default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDBernhard Sick
Person information
- affiliation: University of Kassel, Germany
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
[j52]Denis Huseljic, Marek Herde, Yannick Nagel, Lukas Rauch, Paulius Strimaitis, Bernhard Sick:
The Interplay of Uncertainty Modeling and Deep Active Learning: An Empirical Analysis in Image Classification. Trans. Mach. Learn. Res. 2024 (2024)- [c175]Jens Decke
, Arne Jenß, Bernhard Sick, Christian Gruhl:
An Efficient Multi Quantile Regression Network with Ad Hoc Prevention of Quantile Crossing. ARCS 2024: 51-66 - [c174]Jens Decke, Olaf Wünsch, Bernhard Sick, Christian Gruhl:
From Structured to Unstructured: A Comparative Analysis of Computer Vision and Graph Models in Solving Mesh-Based PDEs. ARCS 2024: 82-96 - [c173]Hannes Reichert, Manuel Hetzel, Andreas Hubert, Konrad Doll, Bernhard Sick:
Sensor Equivariance: A Framework for Semantic Segmentation with Diverse Camera Models. CVPR Workshops 2024: 1254-1261 - [c172]Marek Herde, Lukas Lührs, Denis Huseljic, Bernhard Sick:
Annot-Mix: Learning with Noisy Class Labels from Multiple Annotators via a Mixup Extension. ECAI 2024: 2910-2918 - [c171]Marek Herde, Tuan Pham Minh, Alaa Tharwat, Bernhard Sick:
Tutorial: Interactive Adaptive Learning. IAL@PKDD/ECML 2024: 1-6 - [c170]Lukas Rauch, Denis Huseljic, Moritz Wirth, Jens Decke, Bernhard Sick, Christoph Scholz:
Towards Deep Active Learning in Avian Bioacoustics. IAL@PKDD/ECML 2024: 12-17 - [c169]Paul Hahn, Denis Huseljic, Marek Herde, Bernhard Sick:
General Reusability: Ensuring Long-Term Benefits of Deep Active Learning. IAL@PKDD/ECML 2024: 33-46 - [c168]Jens Decke, Alexander Heinen, Bernhard Sick, Christian Gruhl:
Active Learning with Physics-Informed Graph Neural Networks on Unstructured Meshes. IAL@PKDD/ECML 2024: 68-76 - [c167]Zhixin Huang, Yujiang He, Chandana Priya Nivarthi, Christian Gruhl, Bernhard Sick:
Spatial-Temporal Attention Graph Neural Network with Uncertainty Estimation for Remaining Useful Life Prediction. IJCNN 2024: 1-9 - [c166]Chandana Priya Nivarthi, Zhixin Huang, Christian Gruhl, Bernhard Sick:
Multi-Task Representation Learning with Temporal Attention for Zero-Shot Time Series Anomaly Detection. IJCNN 2024: 1-10 - [c165]Denis Huseljic, Paul Hahn, Marek Herde, Lukas Rauch, Bernhard Sick:
Fast Fishing: Approximating Bait for Efficient and Scalable Deep Active Image Classification. ECML/PKDD (7) 2024: 280-296 - [c164]Diego Botache, Jens Decke, Winfried Ripken, Abhinay Dornipati, Franz Götz-Hahn, Mohamed Ayeb, Bernhard Sick:
Enhancing Multi-objective Optimisation Through Machine Learning-Supported Multiphysics Simulation. ECML/PKDD (10) 2024: 297-312 - [i81]Zhixin Huang, Yujiang He, Bernhard Sick:
Spatio-Temporal Attention Graph Neural Network for Remaining Useful Life Prediction. CoRR abs/2401.15964 (2024) - [i80]Lukas Rauch, Raphael Schwinger, Moritz Wirth, René Heinrich, Jonas Lange, Stefan Kahl, Bernhard Sick, Sven Tomforde, Christoph Scholz:
BirdSet: A Multi-Task Benchmark for Classification in Avian Bioacoustics. CoRR abs/2403.10380 (2024) - [i79]Denis Huseljic, Paul Hahn, Marek Herde, Lukas Rauch, Bernhard Sick:
Fast Fishing: Approximating BAIT for Efficient and Scalable Deep Active Image Classification. CoRR abs/2404.08981 (2024) - [i78]René Heinrich, Bernhard Sick, Christoph Scholz:
AudioProtoPNet: An interpretable deep learning model for bird sound classification. CoRR abs/2404.10420 (2024) - [i77]Florian Heidecker, Ahmad El-Khateeb, Maarten Bieshaar, Bernhard Sick:
Criteria for Uncertainty-based Corner Cases Detection in Instance Segmentation. CoRR abs/2404.11266 (2024) - [i76]Marek Herde, Lukas Lührs, Denis Huseljic, Bernhard Sick:
Annot-Mix: Learning with Noisy Class Labels from Multiple Annotators via a Mixup Extension. CoRR abs/2405.03386 (2024) - [i75]Jens Decke, Arne Jenß, Bernhard Sick, Christian Gruhl:
An Efficient Multi Quantile Regression Network with Ad Hoc Prevention of Quantile Crossing. CoRR abs/2406.00080 (2024) - [i74]Jens Decke, Olaf Wünsch, Bernhard Sick, Christian Gruhl:
From Structured to Unstructured: A Comparative Analysis of Computer Vision and Graph Models in solving Mesh-based PDEs. CoRR abs/2406.00081 (2024) - [i73]Lukas Rauch, Denis Huseljic, Moritz Wirth, Jens Decke, Bernhard Sick, Christoph Scholz:
Towards Deep Active Learning in Avian Bioacoustics. CoRR abs/2406.18621 (2024) - [i72]Martin Braun, Christian Gruhl, Christian A. Hans, Philipp Härtel, Christoph Scholz, Bernhard Sick, Malte Siefert, Florian Steinke, Olaf Stursberg, Sebastian Wende-von Berg:
Predictions and Decision Making for Resilient Intelligent Sustainable Energy Systems. CoRR abs/2407.03021 (2024) - [i71]Mohamed Hassouna, Clara Holzhüter, Pawel Lytaev, Josephine M. Thomas, Bernhard Sick, Christoph Scholz:
Graph Reinforcement Learning in Power Grids: A Survey. CoRR abs/2407.04522 (2024) - [i70]Marek Herde, Denis Huseljic, Lukas Rauch, Bernhard Sick:
dopanim: A Dataset of Doppelganger Animals with Noisy Annotations from Multiple Humans. CoRR abs/2407.20950 (2024) - [i69]Mohammad Wazed Ali, Asif bin Mustafa, Md. Aukerul Moin Shuvo, Bernhard Sick:
Location based Probabilistic Load Forecasting of EV Charging Sites: Deep Transfer Learning with Multi-Quantile Temporal Convolutional Network. CoRR abs/2409.11862 (2024) - [i68]Manuel Hetzel, Hannes Reichert, Konrad Doll, Bernhard Sick:
Reliable Probabilistic Human Trajectory Prediction for Autonomous Applications. CoRR abs/2410.06905 (2024) - 2023
- [j51]Chandana Priya Nivarthi, Stephan Vogt, Bernhard Sick:
Multi-Task Representation Learning for Renewable-Power Forecasting: A Comparative Analysis of Unified Autoencoder Variants and Task-Embedding Dimensions. Mach. Learn. Knowl. Extr. 5(3): 1214-1233 (2023) - [j50]Markus Eider, Bernhard Sick, Andreas Berl:
Context-aware recommendations for extended electric vehicle battery lifetime. Sustain. Comput. Informatics Syst. 37: 100845 (2023) - [j49]Viktor Kress, Fabian Jeske, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Pose and Semantic Map Based Probabilistic Forecast of Vulnerable Road Users' Trajectories. IEEE Trans. Intell. Veh. 8(3): 2592-2603 (2023) - [j48]Marek Herde, Denis Huseljic, Bernhard Sick:
Multi-annotator Deep Learning: A Probabilistic Framework for Classification. Trans. Mach. Learn. Res. 2023 (2023) - [c163]Christian Gruhl, Bernhard Sick:
Self- Integration and Agent Compatibility. ACSOS-C 2023: 71-73 - [c162]Birk Martin Magnussen, Claudius Stern, Bernhard Sick:
Leveraging Repeated Unlabelled Noisy Measurements to Augment Supervised Learning. CIIS 2023: 1-6 - [c161]Christoph Sandrock, Marek Herde, Daniel Kottke, Bernhard Sick:
Exploring the Potential of Optimal Active Learning via a Non-myopic Oracle Policy. DS 2023: 265-276 - [c160]Marek Herde, Denis Huseljic, Bernhard Sick, Ulrich Bretschneider, Sarah Oeste-Reiß:
Who knows best? A Case Study on Intelligent Crowdworker Selection via Deep Learning. IAL@PKDD/ECML 2023: 14-18 - [c159]Denis Huseljic, Marek Herde, Paul Hahn, Bernhard Sick:
Role of Hyperparameters in Deep Active Learning. IAL@PKDD/ECML 2023: 19-24 - [c158]Zhixin Huang, Yujiang He, Marek Herde, Denis Huseljic, Bernhard Sick:
Active Learning with Fast Model Updates and Class-Balanced Selection for Imbalanced Datasets. IAL@PKDD/ECML 2023: 25-45 - [c157]Matthias Aßenmacher, Lukas Rauch, Jann Goschenhofer, Andreas Stephan, Bernd Bischl, Benjamin Roth, Bernhard Sick:
Towards Enhancing Deep Active Learning with Weak Supervision and Constrained Clustering. IAL@PKDD/ECML 2023: 65-73 - [c156]Steven Schreck, Hannes Reichert, Manuel Hetzel, Konrad Doll, Bernhard Sick:
Height Change Feature Based Free Space Detection. ICCMA 2023: 171-176 - [c155]Jasmin Breitenstein, Florian Heidecker, Maria Lyssenko, Daniel Bogdoll, Maarten Bieshaar, J. Marius Zöllner, Bernhard Sick, Tim Fingscheidt:
What Does Really Count? Estimating Relevance of Corner Cases for Semantic Segmentation in Automated Driving. ICCV (Workshops) 2023: 3993-4002 - [c154]Chandana Priya Nivarthi, Bernhard Sick:
Towards Few-Shot Time Series Anomaly Detection with Temporal Attention and Dynamic Thresholding. ICMLA 2023: 1444-1450 - [c153]Jens Decke, Christian Gruhl, Lukas Rauch, Bernhard Sick:
DADO - Low-Cost Query Strategies for Deep Active Design Optimization. ICMLA 2023: 1611-1618 - [c152]Florian Heidecker, Tobias Susetzky, Erich Fuchs, Bernhard Sick:
Context Information for Corner Case Detection in Highly Automated Driving. ITSC 2023: 1522-1529 - [c151]Manuel Hetzel, Hannes Reichert, Günther Reitberger, Erich Fuchs, Konrad Doll, Bernhard Sick:
The IMPTC Dataset: An Infrastructural Multi-Person Trajectory and Context Dataset. IV 2023: 1-7 - [c150]Hannes Reichert, Manuel Hetzel, Steven Schreck, Konrad Doll, Bernhard Sick:
Sensor Equivariance by LiDAR Projection Images. IV 2023: 1-6 - [c149]Lukas Rauch, Matthias Aßenmacher, Denis Huseljic, Moritz Wirth, Bernd Bischl, Bernhard Sick:
ActiveGLAE: A Benchmark for Deep Active Learning with Transformers. ECML/PKDD (1) 2023: 55-74 - [i67]Marek Herde, Denis Huseljic, Bernhard Sick:
Multi-annotator Deep Learning: A Probabilistic Framework for Classification. CoRR abs/2304.02539 (2023) - [i66]Hannes Reichert, Manuel Hetzel, Steven Schreck, Konrad Doll, Bernhard Sick:
Sensor Equivariance by LiDAR Projection Images. CoRR abs/2305.00221 (2023) - [i65]Jens Decke, Olaf Wünsch, Bernhard Sick:
Dataset of a parameterized U-bend flow for Deep Learning Applications. CoRR abs/2305.05216 (2023) - [i64]Florian Heidecker, Ahmad El-Khateeb, Bernhard Sick:
Sampling-based Uncertainty Estimation for an Instance Segmentation Network. CoRR abs/2305.14977 (2023) - [i63]Lukas Rauch, Matthias Aßenmacher, Denis Huseljic, Moritz Wirth, Bernd Bischl, Bernhard Sick:
ActiveGLAE: A Benchmark for Deep Active Learning with Transformers. CoRR abs/2306.10087 (2023) - [i62]Jens Decke, Christian Gruhl, Lukas Rauch, Bernhard Sick:
DADO - Low-Cost Selection Strategies for Deep Active Design Optimization. CoRR abs/2307.04536 (2023) - [i61]Manuel Hetzel, Hannes Reichert, Günther Reitberger, Erich Fuchs, Konrad Doll, Bernhard Sick:
The IMPTC Dataset: An Infrastructural Multi-Person Trajectory and Context Dataset. CoRR abs/2307.06165 (2023) - [i60]Manuel Hetzel, Hannes Reichert, Konrad Doll, Bernhard Sick:
Smart Infrastructure: A Research Junction. CoRR abs/2307.06177 (2023) - [i59]Diego Botache, Kristina Dingel, Rico Huhnstock, Arno Ehresmann, Bernhard Sick:
Unraveling the Complexity of Splitting Sequential Data: Tackling Challenges in Video and Time Series Analysis. CoRR abs/2307.14294 (2023) - [i58]Steven Schreck, Hannes Reichert, Manuel Hetzel, Konrad Doll, Bernhard Sick:
Height Change Feature Based Free Space Detection. CoRR abs/2308.00971 (2023) - [i57]Lukas Rauch, Raphael Schwinger, Moritz Wirth, Bernhard Sick, Sven Tomforde, Christoph Scholz:
Active Bird2Vec: Towards End-to-End Bird Sound Monitoring with Transformers. CoRR abs/2308.07121 (2023) - [i56]Tuan Pham Minh, Jayan Wijesingha, Daniel Kottke, Marek Herde, Denis Huseljic, Bernhard Sick, Michael Wachendorf, Thomas Esch:
Active Label Refinement for Semantic Segmentation of Satellite Images. CoRR abs/2309.06159 (2023) - [i55]Diego Botache, Jens Decke, Winfried Ripken, Abhinay Dornipati, Franz Götz-Hahn, Mohamed Ayeb, Bernhard Sick:
Enhancing Multi-Objective Optimization through Machine Learning-Supported Multiphysics Simulation. CoRR abs/2309.13179 (2023) - 2022
- [j47]Christian Krupitzer, Christian Gruhl, Bernhard Sick, Sven Tomforde:
Proactive hybrid learning and optimisation in self-adaptive systems: The swarm-fleet infrastructure scenario. Inf. Softw. Technol. 145: 106826 (2022) - [j46]Claude Draude, Christian Gruhl, Gerrit Hornung, Jonathan Kropf, Jörn Lamla, Jan Marco Leimeister, Bernhard Sick, Gerd Stumme:
Social Machines. Inform. Spektrum 45(1): 38-42 (2022) - [j45]Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, Klemens Böhm:
Efficient SVDD sampling with approximation guarantees for the decision boundary. Mach. Learn. 111(4): 1349-1375 (2022) - [j44]Tuan Pham, Daniel Kottke, Georg Krempl, Bernhard Sick:
Stream-based active learning for sliding windows under the influence of verification latency. Mach. Learn. 111(6): 2011-2036 (2022) - [c148]Christian Gruhl, Sven Tomforde, Bernhard Sick:
Self-Aware Microsystems. ACSOS-C 2022: 126-127 - [c147]Jens Decke, Jörn Schmeißing, Diego Botache, Maarten Bieshaar, Bernhard Sick, Christian Gruhl:
NDNET: A Unified Framework for Anomaly and Novelty Detection. ARCS 2022: 197-210 - [c146]Tobias Westmeier, Diego Botache, Maarten Bieshaar, Bernhard Sick:
Generating Synthetic Time Series for Machine-Learning-Empowered Monitoring of Electric Motor Test Benches. DSAA 2022: 1-10 - [c145]Chandana Priya Nivarthi, Stephan Vogt, Bernhard Sick:
Unified Autoencoder with Task Embeddings for Multi-Task Learning in Renewable Power Forecasting. ICMLA 2022: 1530-1536 - [c144]Stefan Zernetsch, Hannes Reichert, Viktor Kress, Konrad Doll, Bernhard Sick:
A Holistic View on Probabilistic Trajectory Forecasting - Case Study. Cyclist Intention Detection. IV 2022: 265-272 - [c143]Marek Herde, Denis Huseljic, Jelena Mitrovic, Michael Granitzer, Bernhard Sick:
A Concept for Automated Polarized Web Content Annotation based on Multimodal Active Learning. IAL@PKDD/ECML 2022: 1-6 - [c142]Lukas Rauch, Denis Huseljic, Bernhard Sick:
Enhancing Active Learning with Weak Supervision and Transfer Learning by Leveraging Information and Knowledge Sources. IAL@PKDD/ECML 2022: 27-42 - [c141]Jan Schneegans, Maarten Bieshaar, Bernhard Sick:
A Practical Evaluation of Active Learning Approaches for Object Detection. IAL@PKDD/ECML 2022: 49-67 - [c140]Daniel Kottke, Christoph Sandrock, Georg Krempl, Bernhard Sick:
A Stopping Criterion for Transductive Active Learning. ECML/PKDD (4) 2022: 468-484 - [c139]Kevin Rösch, Florian Heidecker, Julian Truetsch, Kamil Kowol, Clemens Schicktanz, Maarten Bieshaar, Bernhard Sick, Christoph Stiller:
Space, Time, and Interaction: A Taxonomy of Corner Cases in Trajectory Datasets for Automated Driving. SSCI 2022: 86-93 - [i54]Yujiang He, Zhixin Huang, Bernhard Sick:
Design of Explainability Module with Experts in the Loop for Visualization and Dynamic Adjustment of Continual Learning. CoRR abs/2202.06781 (2022) - [i53]Stephan Vogt, Jens Schreiber, Bernhard Sick:
Synthetic Photovoltaic and Wind Power Forecasting Data. CoRR abs/2204.00411 (2022) - [i52]Jens Schreiber, Bernhard Sick:
Model Selection, Adaptation, and Combination for Deep Transfer Learning through Neural Networks in Renewable Energies. CoRR abs/2204.13293 (2022) - [i51]Jens Schreiber, Stephan Vogt, Bernhard Sick:
Task Embedding Temporal Convolution Networks for Transfer Learning Problems in Renewable Power Time-Series Forecast. CoRR abs/2204.13908 (2022) - [i50]Denis Huseljic, Marek Herde, Mehmet Muejde, Bernhard Sick:
A Review of Uncertainty Calibration in Pretrained Object Detectors. CoRR abs/2210.02935 (2022) - [i49]Marek Herde, Zhixin Huang, Denis Huseljic, Daniel Kottke, Stephan Vogt, Bernhard Sick:
Fast Bayesian Updates for Deep Learning with a Use Case in Active Learning. CoRR abs/2210.06112 (2022) - [i48]Kevin Rösch, Florian Heidecker, Julian Truetsch, Kamil Kowol, Clemens Schicktanz, Maarten Bieshaar, Bernhard Sick, Christoph Stiller:
Space, Time, and Interaction: A Taxonomy of Corner Cases in Trajectory Datasets for Automated Driving. CoRR abs/2210.08885 (2022) - 2021
- [j43]Marek Herde, Denis Huseljic, Bernhard Sick, Adrian Calma:
A Survey on Cost Types, Interaction Schemes, and Annotator Performance Models in Selection Algorithms for Active Learning in Classification. IEEE Access 9: 166970-166989 (2021) - [j42]Kristina Dingel, Rico Huhnstock, André Knie, Arno Ehresmann, Bernhard Sick:
AdaPT: Adaptable Particle Tracking for spherical microparticles in lab on chip systems. Comput. Phys. Commun. 262: 107859 (2021) - [j41]Christian Gruhl, Bernhard Sick, Sven Tomforde:
Novelty detection in continuously changing environments. Future Gener. Comput. Syst. 114: 138-154 (2021) - [j40]Sarah Oeste-Reiß, Eva A. C. Bittner, Izabel Cvetkovic, Andreas Günther, Jan Marco Leimeister, Lucas Memmert, Anja Ott, Bernhard Sick, Kathrin Wolter:
Hybride Wissensarbeit. Inform. Spektrum 44(3): 148-152 (2021) - [j39]Daniel Kottke, Marek Herde, Christoph Sandrock, Denis Huseljic, Georg Krempl, Bernhard Sick:
Toward optimal probabilistic active learning using a Bayesian approach. Mach. Learn. 110(6): 1199-1231 (2021) - [c138]Diego Botache, Florian Bethke, Martin Hardieck, Maarten Bieshaar, Ludwig Brabetz, Mohamed Ayeb, Peter Zipf, Bernhard Sick:
Towards Highly Automated Machine-Learning-Empowered Monitoring of Motor Test Stands. ACSOS 2021: 120-130 - [c137]Kristina Dingel, A. Liehr, M. Vogel, S. Degener, David Meier, Thoralf Niendorf, Arno Ehresmann, Bernhard Sick:
AI - Based On The Fly Design of Experiments in Physics and Engineering. ACSOS-C 2021: 150-153 - [c136]Abdul Hannan, Christian Gruhl, Bernhard Sick:
Anomaly based Resilient Network Intrusion Detection using Inferential Autoencoders. CSR 2021: 1-7 - [c135]Felix Möller, Diego Botache, Denis Huseljic, Florian Heidecker, Maarten Bieshaar, Bernhard Sick:
Out-of-Distribution Detection and Generation Using Soft Brownian Offset Sampling and Autoencoders. CVPR Workshops 2021: 46-55 - [c134]Matthias Reuse, Martin Simon, Bernhard Sick:
About the Ambiguity of Data Augmentation for 3D Object Detection in Autonomous Driving. ICCVW 2021: 979-987 - [c133]Daniel Bogdoll, Jasmin Breitenstein, Florian Heidecker, Maarten Bieshaar, Bernhard Sick, Tim Fingscheidt, J. Marius Zöllner:
Description of Corner Cases in Automated Driving: Goals and Challenges. ICCVW 2021: 1023-1028 - [c132]Yujiang He, Zhixin Huang, Bernhard Sick:
Toward Application of Continuous Power Forecasts in a Regional Flexibility Market. IJCNN 2021: 1-8 - [c131]Manuel Hetzel, Hannes Reichert, Konrad Doll, Bernhard Sick:
Smart Infrastructure: A Research Junction. ISC2 2021: 1-4 - [c130]Hannes Reichert, Lukas Lang, Kevin Rösch, Daniel Bogdoll, Konrad Doll, Bernhard Sick, Hans-Christian Reuss, Christoph Stiller, J. Marius Zöllner:
Towards Sensor Data Abstraction of Autonomous Vehicle Perception Systems. ISC2 2021: 1-4 - [c129]Stefan Zernetsch, Oliver Trupp, Viktor Kress, Konrad Doll, Bernhard Sick:
Cyclist Trajectory Forecasts by Incorporation of Multi-View Video Information. ISC2 2021: 1-7 - [c128]Jan Schneegans, Jan Eilbrecht, Stefan Zernetsch, Maarten Bieshaar, Konrad Doll, Olaf Stursberg, Bernhard Sick:
Probabilistic VRU Trajectory Forecasting for Model-Predictive Planning A Case Study: Overtaking Cyclists. IV Workshops 2021: 272-279 - [c127]Florian Heidecker, Jasmin Breitenstein, Kevin Rösch, Jonas Löhdefink, Maarten Bieshaar, Christoph Stiller, Tim Fingscheidt, Bernhard Sick:
An Application-Driven Conceptualization of Corner Cases for Perception in Highly Automated Driving. IV 2021: 644-651 - [c126]Zhixin Huang, Yujiang He, Stephan Vogt, Bernhard Sick:
Uncertainty and Utility Sampling with Pre-Clustering. IAL@PKDD/ECML 2021: 21-34 - [c125]Maarten Bieshaar, Marek Herde, Denis Huseljic, Bernhard Sick:
A Concept for Highly Automated Pre-Labeling via Cross-Domain Label Transfer for Perception in Autonomous Driving. IAL@PKDD/ECML 2021: 65-69 - [c124]Jens Schreiber, Stephan Vogt, Bernhard Sick:
Task Embedding Temporal Convolution Networks for Transfer Learning Problems in Renewable Power Time Series Forecast. ECML/PKDD (4) 2021: 118-134 - [c123]Maarten Bieshaar, Stefan Zernetsch, Katharina Riepe, Konrad Doll, Bernhard Sick:
Cyclist Motion State Forecasting - Going beyond Detection. SSCI 2021: 1-8 - [d2]Viktor Kress, Stefan Zernetsch, Maarten Bieshaar, Günther Reitberger, Erich Fuchs, Konrad Doll, Bernhard Sick:
Pedestrians and Cyclists in Road Traffic: Trajectories, 3D Poses and Semantic Maps. Zenodo, 2021
- [d1]Viktor Kress, Stefan Zernetsch, Hannes Reichert, Manuel Hetzel, Maarten Bieshaar, Günther Reitberger, Erich Fuchs, Konrad Doll, Bernhard Sick:
Aschaffenburg Pose Dataset. Zenodo, 2021 - [i47]Yujiang He, Bernhard Sick:
CLeaR: An Adaptive Continual Learning Framework for Regression Tasks. CoRR abs/2101.00926 (2021) - [i46]Florian Heidecker, Jasmin Breitenstein, Kevin Rösch, Jonas Löhdefink, Maarten Bieshaar, Christoph Stiller, Tim Fingscheidt, Bernhard Sick:
An Application-Driven Conceptualization of Corner Cases for Perception in Highly Automated Driving. CoRR abs/2103.03678 (2021) - [i45]Stefan Zernetsch, Hannes Reichert, Viktor Kress, Konrad Doll, Bernhard Sick:
Cyclist Intention Detection: A Probabilistic Approach. CoRR abs/2104.09176 (2021) - [i44]Felix Möller, Diego Botache, Denis Huseljic, Florian Heidecker, Maarten Bieshaar, Bernhard Sick:
Out-of-distribution Detection and Generation using Soft Brownian Offset Sampling and Autoencoders. CoRR abs/2105.02965 (2021) - [i43]Hannes Reichert, Lukas Lang, Kevin Rösch, Daniel Bogdoll, Konrad Doll, Bernhard Sick, Hans-Christian Reuss, Christoph Stiller, J. Marius Zöllner:
Towards Sensor Data Abstraction of Autonomous Vehicle Perception Systems. CoRR abs/2105.06896 (2021) - [i42]Viktor Kress, Fabian Jeske, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Pose and Semantic Map Based Probabilistic Forecast of Vulnerable Road Users' Trajectories. CoRR abs/2106.02598 (2021) - [i41]Stefan Zernetsch, Oliver Trupp, Viktor Kress, Konrad Doll, Bernhard Sick:
Cyclist Trajectory Forecasts by Incorporation of Multi-View Video Information. CoRR abs/2106.15991 (2021) - [i40]Daniel Kottke, Georg Krempl, Marianne Stecklina, Cornelius Styp von Rekowski, Tim Sabsch, Tuan Pham Minh, Matthias Deliano, Myra Spiliopoulou, Bernhard Sick:
Probabilistic Active Learning for Active Class Selection. CoRR abs/2108.03891 (2021) - [i39]Kristina Dingel, Thorsten Otto, Lutz Marder, Lars Funke, Arne Held, Sara Savio, Andreas Hans, Gregor Hartmann, David Meier, Jens Viefhaus, Bernhard Sick, Arno Ehresmann, Markus Ilchen, Wolfram Helml:
Toward AI-enhanced online-characterization and shaping of ultrashort X-ray free-electron laser pulses. CoRR abs/2108.13979 (2021) - [i38]Daniel Bogdoll, Jasmin Breitenstein, Florian Heidecker, Maarten Bieshaar, Bernhard Sick, Tim Fingscheidt, J. Marius Zöllner:
Description of Corner Cases in Automated Driving: Goals and Challenges. CoRR abs/2109.09607 (2021) - [i37]Marek Herde, Denis Huseljic, Bernhard Sick, Adrian Calma:
A Survey on Cost Types, Interaction Schemes, and Annotator Performance Models in Selection Algorithms for Active Learning in Classification. CoRR abs/2109.11301 (2021) - [i36]Inga Löser, Martin Braun, Christian Gruhl, Jan-Hendrik Menke, Bernhard Sick, Sven Tomforde:
Towards Organic Distribution Systems - The Vision of Self-Configuring, Self-Organising, Self-Healing, and Self-Optimising Power Distribution Management. CoRR abs/2112.07507 (2021) - 2020
- [j38]Michael Goldhammer, Sebastian Köhler, Stefan Zernetsch, Konrad Doll, Bernhard Sick, Klaus Dietmayer:
Intentions of Vulnerable Road Users - Detection and Forecasting by Means of Machine Learning. IEEE Trans. Intell. Transp. Syst. 21(7): 3035-3045 (2020) - [c122]Christian Gruhl, Jörn Schmeißing, Sven Tomforde, Bernhard Sick:
Normal-Wishart Clustering for Novelty Detection. ACSOS Companion 2020: 64-69 - [c121]Sven Tomforde, Christian Gruhl, Bernhard Sick:
A Swarm-fleet Infrastructure as a Scenario for Proactive, Hybrid Adaptation of System Behaviour. ACSOS Companion 2020: 166-169 - [c120]Nicolas Scheiner, Florian Kraus, Fangyin Wei, Buu Phan, Fahim Mannan, Nils Appenrodt, Werner Ritter, Jürgen Dickmann, Klaus Dietmayer, Bernhard Sick, Felix Heide:
Seeing Around Street Corners: Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler Radar. CVPR 2020: 2065-2074 - [c119]Nicolas Scheiner, Ole Schumann, Florian Kraus, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
Off-the-shelf sensor vs. experimental radar - How much resolution is necessary in automotive radar classification? FUSION 2020: 1-8 - [c118]Viktor Kress, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Pose Based Trajectory Forecast of Vulnerable Road Users Using Recurrent Neural Networks. ICPR Workshops (1) 2020: 57-71 - [c117]Florian Heidecker, Abdul Hannan, Maarten Bieshaar, Bernhard Sick:
Towards Corner Case Detection by Modeling the Uncertainty of Instance Segmentation Networks. ICPR Workshops (4) 2020: 361-374 - [c116]Jan Schneegans, Maarten Bieshaar, Florian Heidecker, Bernhard Sick:
Intelligent and Interactive Video Annotation for Instance Segmentation Using Siamese Neural Networks. ICPR Workshops (4) 2020: 375-389 - [c115]Florian Heidecker, Christian Gruhl, Bernhard Sick:
Novelty Based Driver Identification on RR Intervals from ECG Data. ICPR Workshops (4) 2020: 407-421 - [c114]Stefan Zernetsch, Steven Schreck, Viktor Kress, Konrad Doll, Bernhard Sick:
Image Sequence Based Cyclist Action Recognition Using Multi-Stream 3D Convolution. ICPR 2020: 2620-2626 - [c113]Jens Schreiber, Bernhard Sick:
Emerging Relation Network and Task Embedding for Multi-Task Regression Problems. ICPR 2020: 2663-2670 - [c112]Denis Huseljic, Bernhard Sick, Marek Herde, Daniel Kottke:
Separation of Aleatoric and Epistemic Uncertainty in Deterministic Deep Neural Networks. ICPR 2020: 9172-9179 - [c111]Christian Haase-Schütz, Rainer Stal, Heinz Hertlein, Bernhard Sick:
Iterative Label Improvement: Robust Training by Confidence Based Filtering and Dataset Partitioning. ICPR 2020: 9483-9490 - [c110]Marek Herde, Daniel Kottke, Denis Huseljic, Bernhard Sick:
Multi-Annotator Probabilistic Active Learning. ICPR 2020: 10281-10288 - [c109]Yujiang He, Janosch Henze, Bernhard Sick:
Forecasting Power Grid States for Regional Energy Markets with Deep Neural Networks. IJCNN 2020: 1-8 - [c108]Tuan Pham Minh, Daniel Kottke, Anna Tsarenko, Christian Gruhl, Bernhard Sick:
Improving Self-Adaptation For Multi-Sensor Activity Recognition with Active Learning. IJCNN 2020: 1-8 - [c107]Viktor Kress, Steven Schreck, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Pose Based Action Recognition of Vulnerable Road Users Using Recurrent Neural Networks. SSCI 2020: 2723-2730 - [i35]Christian Haase-Schütz, Rainer Stal, Heinz Hertlein, Bernhard Sick:
Trust Your Model: Iterative Label Improvement and Robust Training by Confidence Based Filtering and Dataset Partitioning. CoRR abs/2002.02705 (2020) - [i34]Stephan Deist, Jens Schreiber, Maarten Bieshaar, Bernhard Sick:
Extended Coopetitive Soft Gating Ensemble. CoRR abs/2004.14026 (2020) - [i33]Jens Schreiber, Bernhard Sick:
Emerging Relation Network and Task Embedding for Multi-Task Regression Problems. CoRR abs/2004.14034 (2020) - [i32]Daniel Kottke, Marek Herde, Christoph Sandrock, Denis Huseljic, Georg Krempl, Bernhard Sick:
Toward Optimal Probabilistic Active Learning Using a Bayesian Approach. CoRR abs/2006.01732 (2020) - [i31]Nicolas Scheiner, Ole Schumann, Florian Kraus, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
Off-the-shelf sensor vs. experimental radar - How much resolution is necessary in automotive radar classification? CoRR abs/2006.05485 (2020) - [i30]Adrian Englhardt, Holger Trittenbach, Daniel Kottke, Bernhard Sick, Klemens Böhm:
Efficient SVDD Sampling with Approximation Guarantees for the Decision Boundary. CoRR abs/2009.13853 (2020) - [i29]Maarten Bieshaar, Jens Schreiber, Stephan Vogt, André Gensler, Bernhard Sick:
Quantile Surfaces - Generalizing Quantile Regression to Multivariate Targets. CoRR abs/2010.05898 (2020)
2010 – 2019
- 2019
- [c106]Viktor Kress, Janis Jung, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Start Intention Detection of Cyclists using an LSTM Network. GI-Jahrestagung (Workshops) 2019: 219-228 - [c105]Diego Botache, Dandan Liu, Maarten Bieshaar, Bernhard Sick:
Early Pedestrian Movement Detection Using Smart Devices Based on Human Activity Recognition. GI-Jahrestagung (Workshops) 2019: 229-238 - [c104]Immanuel König, Erik Heilmann, Janosch Henze, Klaus David, Heike Wetzel, Bernhard Sick:
Using grid supporting flexibility in electricity distribution networks. GI-Jahrestagung 2019: 531-544 - [c103]Jens Schreiber, Artjom Buschin, Bernhard Sick:
Influences in Forecast Errors for Wind and Photovoltaic Power: A Study on Machine Learning Models. GI-Jahrestagung 2019: 585-598 - [c102]Jens Schreiber, Maik Jessulat, Bernhard Sick:
Generative Adversarial Networks for Operational Scenario Planning of Renewable Energy Farms: A Study on Wind and Photovoltaic. ICANN (3) 2019: 550-564 - [c101]Christoph Sandrock, Marek Herde, Adrian Calma, Daniel Kottke, Bernhard Sick:
Combining Self-reported Confidences from Uncertain Annotators to Improve Label Quality. IJCNN 2019: 1-8 - [c100]Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
A Multi-Stage Clustering Framework for Automotive Radar Data. ITSC 2019: 2060-2067 - [c99]Viktor Kress, Janis Jung, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Pose Based Start Intention Detection of Cyclists. ITSC 2019: 2381-2386 - [c98]Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
Radar-based Road User Classification and Novelty Detection with Recurrent Neural Network Ensembles. IV 2019: 722-729 - [c97]Stefan Zernetsch, Hannes Reichert, Viktor Kress, Konrad Doll, Bernhard Sick:
Trajectory Forecasts with Uncertainties of Vulnerable Road Users by Means of Neural Networks. IV 2019: 810-815 - [c96]Viktor Kress, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Pose Based Trajectory Forecast of Vulnerable Road Users. SSCI 2019: 1200-1207 - [e5]Claude Draude, Martin Lange, Bernhard Sick:
49. Jahrestagung der Gesellschaft für Informatik, 50 Jahre Gesellschaft für Informatik - Informatik für Gesellschaft, INFORMATIK 2019 - Workshops, Kassel, Germany, September 23-26, 2019. LNI P-295, GI 2019, ISBN 978-3-88579-689-3 [contents] - [i28]Daniel Kottke, Jim Schellinger, Denis Huseljic, Bernhard Sick:
Limitations of Assessing Active Learning Performance at Runtime. CoRR abs/1901.10338 (2019) - [i27]Tom Hanika, Marek Herde, Jochen Kuhn, Jan Marco Leimeister, Paul Lukowicz, Sarah Oeste-Reiß, Albrecht Schmidt, Bernhard Sick, Gerd Stumme, Sven Tomforde, Katharina Anna Zweig:
Collaborative Interactive Learning - A clarification of terms and a differentiation from other research fields. CoRR abs/1905.07264 (2019) - [i26]Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
Automated Ground Truth Estimation of Vulnerable Road Users in Automotive Radar Data Using GNSS. CoRR abs/1905.11219 (2019) - [i25]Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
Radar-based Feature Design and Multiclass Classification for Road User Recognition. CoRR abs/1905.11256 (2019) - [i24]Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
Radar-based Road User Classification and Novelty Detection with Recurrent Neural Network Ensembles. CoRR abs/1905.11703 (2019) - [i23]Nicolas Scheiner, Stefan Haag, Nils Appenrodt, Bharanidhar Duraisamy, Jürgen Dickmann, Martin Fritzsche, Bernhard Sick:
Automated Ground Truth Estimation For Automotive Radar Tracking Applications With Portable GNSS And IMU Devices. CoRR abs/1905.11987 (2019) - [i22]Jens Schreiber, Artjom Buschin, Bernhard Sick:
Influences in Forecast Errors for Wind and Photovoltaic Power: A Study on Machine Learning Models. CoRR abs/1905.13668 (2019) - [i21]Jens Schreiber, Maik Jessulat, Bernhard Sick:
Generative Adversarial Networks for Operational Scenario Planning of Renewable Energy Farms: A Study on Wind and Photovoltaic. CoRR abs/1906.00662 (2019) - [i20]Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
A Multi-Stage Clustering Framework for Automotive Radar Data. CoRR abs/1907.03511 (2019) - [i19]Nicolas Scheiner, Florian Kraus, Fangyin Wei, Buu Phan, Fahim Mannan, Nils Appenrodt, Werner Ritter, Jürgen Dickmann, Klaus Dietmayer, Bernhard Sick, Felix Heide:
Seeing Around Street Corners: Non-Line-of-Sight Detection and Tracking In-the-Wild Using Doppler Radar. CoRR abs/1912.06613 (2019) - 2018
- [j37]Sebastian Breker, Jan Rentmeister, Bernhard Sick, Martin Braun:
Hosting capacity of low-voltage grids for distributed generation: Classification by means of machine learning techniques. Appl. Soft Comput. 70: 195-207 (2018) - [j36]Martin Jänicke, Bernhard Sick, Sven Tomforde:
Self-Adaptive Multi-Sensor Activity Recognition Systems Based on Gaussian Mixture Models. Informatics 5(3): 38 (2018) - [j35]Bernhard Sick, Sarah Oeste-Reiß, Albrecht Schmidt, Sven Tomforde, Katharina Anna Zweig:
Collaborative Interactive Learning. Inform. Spektrum 41(1): 52-55 (2018) - [j34]Adrian Calma, Tobias Reitmaier, Bernhard Sick:
Semi-supervised active learning for support vector machines: A novel approach that exploits structure information in data. Inf. Sci. 456: 13-33 (2018) - [j33]Christian Gruhl, Bernhard Sick:
Novelty detection with CANDIES: a holistic technique based on probabilistic models. Int. J. Mach. Learn. Cybern. 9(6): 927-945 (2018) - [j32]Andre Gensler, Bernhard Sick:
Performing event detection in time series with SwiftEvent: an algorithm with supervised learning of detection criteria. Pattern Anal. Appl. 21(2): 543-562 (2018) - [j31]Sven Tomforde, Jan Kantert, Christian Müller-Schloer, Sebastian Bödelt, Bernhard Sick:
Comparing the Effects of Disturbances in Self-adaptive Systems - A Generalised Approach for the Quantification of Robustness. Trans. Comput. Collect. Intell. 28: 193-220 (2018) - [j30]Maarten Bieshaar, Stefan Zernetsch, Andreas Hubert, Bernhard Sick, Konrad Doll:
Cooperative Starting Movement Detection of Cyclists Using Convolutional Neural Networks and a Boosted Stacking Ensemble. IEEE Trans. Intell. Veh. 3(4): 534-544 (2018) - [c95]Maarten Bieshaar, Malte Depping, Jan Schneegans, Bernhard Sick:
Starting Movement Detection of Cyclists Using Smart Devices. DSAA 2018: 313-322 - [c94]Adrian Calma, Sarah Oeste-Reiß, Bernhard Sick, Jan Marco Leimeister:
Leveraging the Potentials of Dedicated Collaborative Interactive Learning: Conceptual Foundations to Overcome Uncertainty by Human-Machine Collaboration. HICSS 2018: 1-9 - [c93]Martin Jänicke, Viktor Schmidt, Bernhard Sick, Sven Tomforde, Paul Lukowicz:
Hijacked Smart Devices - Methodical Foundations for Autonomous Theft Awareness based on Activity Recognition and Novelty Detection. ICAART (2) 2018: 131-142 - [c92]Martin Jänicke, Viktor Schmidt, Bernhard Sick, Sven Tomforde, Paul Lukowicz, Jörn Schmeißing:
Smart Device Stealing and CANDIES. ICAART (Revised Selected Papers) 2018: 247-273 - [c91]Adrian Calma, Moritz Stolz, Daniel Kottke, Sven Tomforde, Bernhard Sick:
Active Learning With Realistic Data - A Case Study. IJCNN 2018: 1-8 - [c90]Marek Herde, Daniel Kottke, Adrian Calma, Maarten Bieshaar, Stephan Deist, Bernhard Sick:
Active Sorting - An Efficient Training of a Sorting Robot with Active Learning Techniques. IJCNN 2018: 1-8 - [c89]Daniel Kottke, Adrian Calma, Denis Huseljic, Christoph Sandrock, George Kachergis, Bernhard Sick:
The Other Human in The Loop - A Pilot Study to Find Selection Strategies for Active Learning. IJCNN 2018: 1-8 - [c88]Günther Reitberger, Maarten Bieshaar, Stefan Zernetsch, Konrad Doll, Bernhard Sick, Erich Fuchs:
Cooperative Tracking of Cyclists Based on Smart Devices and Infrastructure. ITSC 2018: 436-443 - [c87]Stefan Zernetsch, Viktor Kress, Bernhard Sick, Konrad Doll:
Early Start Intention Detection of Cyclists Using Motion History Images and a Deep Residual Network. Intelligent Vehicles Symposium 2018: 1-6 - [c86]Nicolas Scheiner, Nils Appenrodt, Jürgen Dickmann, Bernhard Sick:
Radar-based Feature Design and Multiclass Classification for Road User Recognition. Intelligent Vehicles Symposium 2018: 779-786 - [c85]Theresa Kromat, Tobias Dehling, Reinhold Haux, Christoph Peters, Bernhard Sick, Sven Tomforde, Klaus-Hendrik Wolf, Ali Sunyaev:
Gestaltungsraum für proaktive Smart Homes zur Gesundheitsförderung. MKWI 2018: 695-707 - [c84]Andreas Jahn, Sven Tomforde, Michel Morold, Klaus David, Bernhard Sick:
Towards Cooperative Self-adapting Activity Recognition. PECCS 2018: 215-222 - [c83]Janosch Henze, Stephan Kutzner, Bernhard Sick:
Sampling Strategies for Representative Time Series in Load Flow Calculations. DARE@PKDD/ECML 2018: 27-48 - [c82]Henner Heck, Bernhard Sick, Sven Tomforde:
Security Issues in Self-Improving System Integration - Challenges and Solution Strategies. FAS*W@SASO/ICAC 2018: 176-181 - [c81]Jens Schreiber, Maarten Bieshaar, Andre Gensler, Bernhard Sick, Stephan Deist:
Coopetitive Soft Gating Ensemble. FAS*W@SASO/ICAC 2018: 190-197 - [c80]Christian Gruhl, Sven Tomforde, Bernhard Sick:
Aspects of Measuring and Evaluating the Integration Status of a (Sub-)System at Runtime. FAS*W@SASO/ICAC 2018: 198-203 - [c79]Viktor Kress, Janis Jung, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Human Pose Estimation in Real Traffic Scenes. SSCI 2018: 518-523 - [e4]Georg Krempl, Vincent Lemaire, Daniel Kottke, Adrian Calma, Andreas Holzinger, Robi Polikar, Bernhard Sick:
Proceedings of the Workshop on Interactive Adaptive Learning co-located with European Conference on Machine Learning (ECML 2018) and Principles and Practice of Knowledge Discovery in Databases (PKDD 2018), Dublin, Ireland, September 10th, 2018. CEUR Workshop Proceedings 2192, CEUR-WS.org 2018 [contents] - [i18]Günther Reitberger, Stefan Zernetsch, Maarten Bieshaar, Bernhard Sick, Konrad Doll, Erich Fuchs:
Cooperative Tracking of Cyclists Based on Smart Devices and Infrastructure. CoRR abs/1803.02096 (2018) - [i17]Stefan Zernetsch, Viktor Kress, Bernhard Sick, Konrad Doll:
Early Start Intention Detection of Cyclists Using Motion History Images and a Deep Residual Network. CoRR abs/1803.02242 (2018) - [i16]Maarten Bieshaar, Günther Reitberger, Viktor Kreß, Stefan Zernetsch, Konrad Doll, Erich Fuchs, Bernhard Sick:
Highly Automated Learning for Improved Active Safety of Vulnerable Road Users. CoRR abs/1803.03479 (2018) - [i15]Maarten Bieshaar, Stefan Zernetsch, Andreas Hubert, Bernhard Sick, Konrad Doll:
Cooperative Starting Movement Detection of Cyclists Using Convolutional Neural Networks and a Boosted Stacking Ensemble. CoRR abs/1803.03487 (2018) - [i14]Michael Goldhammer, Sebastian Köhler, Stefan Zernetsch, Konrad Doll, Bernhard Sick, Klaus Dietmayer:
Intentions of Vulnerable Road Users - Detection and Forecasting by Means of Machine Learning. CoRR abs/1803.03577 (2018) - [i13]Stephan Deist, Maarten Bieshaar, Jens Schreiber, Andre Gensler, Bernhard Sick:
Coopetitive Soft Gating Ensemble. CoRR abs/1807.01020 (2018) - [i12]Maarten Bieshaar, Malte Depping, Jan Schneegans, Bernhard Sick:
Starting Movement Detection of Cyclists Using Smart Devices. CoRR abs/1808.04449 (2018) - [i11]Jens Schreiber, Bernhard Sick:
Quantifying the Influences on Probabilistic Wind Power Forecasts. CoRR abs/1808.04750 (2018) - [i10]Maarten Bieshaar, Günther Reitberger, Stefan Zernetsch, Bernhard Sick, Erich Fuchs, Konrad Doll:
Detecting Intentions of Vulnerable Road Users Based on Collective Intelligence. CoRR abs/1809.03916 (2018) - 2017
- [c78]Jan Kantert, Sven Tomforde, Christian Müller-Schloer, Sarah Edenhofer, Bernhard Sick:
Quantitative Robustness - A Generalised Approach to Compare the Impact of Disturbances in Self-organising Systems. ICAART (1) 2017: 39-50 - [c77]Sven Tomforde, Jan Kantert, Bernhard Sick:
Measuring Self-organisation at Runtime - A Quantification Method based on Divergence Measures. ICAART (1) 2017: 96-106 - [c76]Bernhard Schlegel, Bernhard Sick:
Dealing with Class Imbalance the Scalable Way: Evaluation of Various Techniques Based on Classification Grade and Computational Complexity. ICDM Workshops 2017: 69-78 - [c75]Klaus-Hendrik Wolf, Tobias Dehling, Reinhold Haux, Bernhard Sick, Ali Sunyaev, Sven Tomforde:
On Methodological and Technological Challenges for Proactive Health Management in Smart Homes. ICIMTH 2017: 209-212 - [c74]Maarten Bieshaar, Stefan Zernetsch, Malte Depping, Bernhard Sick, Konrad Doll:
Cooperative starting intention detection of cyclists based on smart devices and infrastructure. ITSC 2017: 1-8 - [c73]Andreas Hubert, Stefan Zernetsch, Konrad Doll, Bernhard Sick:
Cyclists' starting behavior at intersections. Intelligent Vehicles Symposium 2017: 1071-1077 - [c72]Daniel Kottke, Adrian Calma, Denis Huseljic, Georg Krempl, Bernhard Sick:
Challenges of Reliable, Realistic and Comparable Active Learning Evaluation. IAL@PKDD/ECML 2017: 2-14 - [c71]Adrian Calma, Bernhard Sick:
Simulation of Annotators for Active Learning: Uncertain Oracles. IAL@PKDD/ECML 2017: 49-58 - [c70]Janosch Henze, Tanja Kneiske, Martin Braun, Bernhard Sick:
Identifying Representative Load Time Series for Load Flow Calculations. DARE@PKDD/ECML 2017: 83-93 - [c69]Adrian Calma, Daniel Kottke, Bernhard Sick, Sven Tomforde:
Learning to Learn: Dynamic Runtime Exploitation of Various Knowledge Sources and Machine Learning Paradigms. FAS*W@SASO/ICCAC 2017: 109-116 - [c68]Jan Eilbrecht, Maarten Bieshaar, Stefan Zernetsch, Konrad Doll, Bernhard Sick, Olaf Stursberg:
Model-predictive planning for autonomous vehicles anticipating intentions of vulnerable road users by artificial neural networks. SSCI 2017: 1-8 - [c67]Andre Gensler, Bernhard Sick:
Probabilistic wind power forecasting: A multi-scheme ensemble technique with gradual coopetitive soft gating. SSCI 2017: 1-10 - [e3]Georg Krempl, Vincent Lemaire, Robi Polikar, Bernhard Sick, Daniel Kottke, Adrian Calma:
Proceedings of the Workshop and Tutorial on Interactive Adaptive Learning co-located with European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD 2017), Skopje, Macedonia, September 18, 2017. CEUR Workshop Proceedings 1924, CEUR-WS.org 2017 [contents] - [i9]Sven Tomforde, Bernhard Sick, Christian Müller-Schloer:
Organic Computing in the Spotlight. CoRR abs/1701.08125 (2017) - [i8]David Bannach, Martin Jänicke, Vitor F. Rey, Sven Tomforde, Bernhard Sick, Paul Lukowicz:
Self-Adaptation of Activity Recognition Systems to New Sensors. CoRR abs/1701.08528 (2017) - 2016
- [j29]Dominik Fisch, Christian Gruhl, Edgar Kalkowski, Bernhard Sick, Seppo J. Ovaska:
Towards automation of knowledge understanding: An approach for probabilistic generative classifiers. Inf. Sci. 370-371: 476-496 (2016) - [c66]Gerald Pirkl, Peter Hevesi, Paul Lukowicz, Pascal Klein, Carina Heisel, Sebastian Gröber, Jochen Kuhn, Bernhard Sick:
Any problems? a wearable sensor-based platform for representational learning-analytics. UbiComp Adjunct 2016: 353-356 - [c65]Martin Jänicke, Sven Tomforde, Bernhard Sick:
Towards Self-Improving Activity Recognition Systems Based on Probabilistic, Generative Models. ICAC 2016: 285-291 - [c64]Gernot Bahle, Adrian Calma, Jan Marco Leimeister, Paul Lukowicz, Sarah Oeste-Reiss, Tobias Reitmaier, Albrecht Schmidt, Bernhard Sick, Gerd Stumme, Katharina Anna Zweig:
Lifelong Learning and Collaboration of Smart Technical Systems in Open-Ended Environments - Opportunistic Collaborative Interactive Learning. ICAC 2016: 315-324 - [c63]Edgar Kalkowski, Bernhard Sick:
Correlation of Ontology-Based Semantic Similarity and Human Judgement for a Domain Specific Fashion Ontology. ICWE 2016: 207-224 - [c62]Sebastian Breker, Bernhard Sick:
Combination of uncertain ordinal expert statements: The combination rule EIDMR and its application to low-voltage grid classification with SVM. IJCNN 2016: 2164-2173 - [c61]Adrian Calma, Tobias Reitmaier, Bernhard Sick:
Resp-kNN: A probabilistic k-nearest neighbor classifier for sparsely labeled data. IJCNN 2016: 4040-4047 - [c60]Andre Gensler, Bernhard Sick:
Forecasting wind power - an ensemble technique with gradual coopetitive weighting based on weather situation. IJCNN 2016: 4976-4984 - [c59]Stefan Zernetsch, Sascha Kohnen, Michael Goldhammer, Konrad Doll, Bernhard Sick:
Trajectory prediction of cyclists using a physical model and an artificial neural network. Intelligent Vehicles Symposium 2016: 833-838 - [c58]Matthias Kreil, Bernhard Sick, Paul Lukowicz:
Coping with variability in motion based activity recognition. iWOAR 2016: 4:1-4:8 - [c57]Henner Heck, Stefan Rudolph, Christian Gruhl, Arno Wacker, Jörg Hähner, Bernhard Sick, Sven Tomforde:
Towards Autonomous Self-Tests at Runtime. FAS*W@SASO/ICCAC 2016: 98-99 - [c56]Andre Gensler, Bernhard Sick, Vitali Pankraz:
An analog ensemble-based similarity search technique for solar power forecasting. SMC 2016: 2850-2857 - [c55]Andre Gensler, Janosch Henze, Bernhard Sick, Nils Raabe:
Deep Learning for solar power forecasting - An approach using AutoEncoder and LSTM Neural Networks. SMC 2016: 2858-2865 - [c54]Andre Gensler, Bernhard Sick, Stephan Vogt:
A review of deterministic error scores and normalization techniques for power forecasting algorithms. SSCI 2016: 1-9 - [c53]Bernhard Schlegel, Bernhard Sick:
Design and optimization of an autonomous feature selection pipeline for high dimensional, heterogeneous feature spaces. SSCI 2016: 1-9 - [i7]Christian Gruhl, Bernhard Sick:
Detecting Novel Processes with CANDIES - An Holistic Novelty Detection Technique based on Probabilistic Models. CoRR abs/1605.05628 (2016) - [i6]Dominik Fisch, Christian Gruhl, Edgar Kalkowski, Bernhard Sick, Seppo J. Ovaska:
Towards Automation of Knowledge Understanding: An Approach for Probabilistic Generative Classifiers. CoRR abs/1605.06377 (2016) - [i5]Christian Gruhl, Bernhard Sick:
Variational Bayesian Inference for Hidden Markov Models With Multivariate Gaussian Output Distributions. CoRR abs/1605.08618 (2016) - [i4]Tobias Reitmaier, Adrian Calma, Bernhard Sick:
Semi-Supervised Active Learning for Support Vector Machines: A Novel Approach that Exploits Structure Information in Data. CoRR abs/1610.03995 (2016) - 2015
- [j28]Tobias Reitmaier, Adrian Calma, Bernhard Sick:
Transductive active learning - A new semi-supervised learning approach based on iteratively refined generative models to capture structure in data. Inf. Sci. 293: 275-298 (2015) - [j27]Tobias Reitmaier, Bernhard Sick:
The responsibility weighted Mahalanobis kernel for semi-supervised training of support vector machines for classification. Inf. Sci. 323: 179-198 (2015) - [c52]Christian Gruhl, Bernhard Sick, Arno Wacker, Sven Tomforde, Jörg Hähner:
A building block for awareness in technical systems: Online novelty detection and reaction with an application in intrusion detection. iCAST 2015: 194-200 - [c51]Stefan Rudolph, Sven Tomforde, Bernhard Sick, Jörg Hähner:
A Mutual Influence Detection Algorithm for Systems with Local Performance Measurement. SASO 2015: 144-149 - [c50]Edgar Kalkowski, Bernhard Sick:
Using Ontology-Based Similarity Measures to Find Training Data for Problems with Sparse Data. SMC 2015: 1693-1699 - [c49]Andre Gensler, Thiemo Gruber, Bernhard Sick:
Fast Feature Extraction for Time Series Analysis Using Least-Squares Approximations with Orthogonal Basis Functions. TIME 2015: 29-37 - [c48]Andreas Jahn, Sian Lun Lau, Klaus David, Bernhard Sick:
A Toolchain for Context Recognition: Automating the Investigation of a Multitude of Parameter Sets. VTC Fall 2015: 1-5 - [i3]Tobias Reitmaier, Bernhard Sick:
The Responsibility Weighted Mahalanobis Kernel for Semi-Supervised Training of Support Vector Machines for Classification. CoRR abs/1502.04033 (2015) - [i2]Adrian Calma, Tobias Reitmaier, Bernhard Sick, Paul Lukowicz:
A New Vision of Collaborative Active Learning. CoRR abs/1504.00284 (2015) - 2014
- [j26]Sven Tomforde, Jörg Hähner, Bernhard Sick:
Interwoven Systems. Inform. Spektrum 37(5): 483-487 (2014) - [j25]Helmuth Pree, Benjamin Herwig, Thiemo Gruber, Bernhard Sick, Klaus David, Paul Lukowicz:
On general purpose time series similarity measures and their use as kernel functions in support vector machines. Inf. Sci. 281: 478-495 (2014) - [j24]Dominik Fisch, Edgar Kalkowski, Bernhard Sick:
Knowledge Fusion for Probabilistic Generative Classifiers with Data Mining Applications. IEEE Trans. Knowl. Data Eng. 26(3): 652-666 (2014) - [c47]Sven Tomforde, Jörg Hähner, Hella Seebach, Wolfgang Reif, Bernhard Sick, Arno Wacker, Ingo Scholtes:
Engineering and Mastering Interwoven Systems. ARCS Workshops 2014: 1-8 - [c46]Andre Gensler, Bernhard Sick, Jens Willkomm:
Temporal data analytics based on eigenmotif and shape space representations of time series. ChinaSIP 2014: 753-757 - [c45]Thomas Stone, Olga Birth, Andre Gensler, Andreas Huber, Martin Jänicke, Bernhard Sick:
Location based learning of user behavior for proactive recommender systems in car comfort functions. GI-Jahrestagung 2014: 2121-2132 - [c44]Michael Goldhammer, Konrad Doll, Ulrich Brunsmann, Andre Gensler, Bernhard Sick:
Pedestrian's Trajectory Forecast in Public Traffic with Artificial Neural Networks. ICPR 2014: 4110-4115 - [c43]Michael Goldhammer, Andreas Hubert, Sebastian Köhler, Klaus Zindler, Ulrich Brunsmann, Konrad Doll, Bernhard Sick:
Analysis on termination of pedestrians' gait at urban intersections. ITSC 2014: 1758-1763 - [c42]Andre Gensler, Bernhard Sick:
Novel Criteria to Measure Performance of Time Series Segmentation Techniques. LWA 2014: 193-204 - [c41]Matthias Kreil, Bernhard Sick, Paul Lukowicz:
Dealing with human variability in motion based, wearable activity recognition. PerCom Workshops 2014: 36-40 - [c40]Martin Jänicke, Bernhard Sick, Paul Lukowicz, David Bannach:
Self-Adapting Multi-sensor Systems: A Concept for Self-Improvement and Self-Healing Techniques. SASO Workshops 2014: 128-136 - [c39]Sven Tomforde, Jörg Hähner, Sebastian von Mammen, Christian Gruhl, Bernhard Sick, Kurt Geihs:
"Know Thyself" - Computational Self-Reflection in Intelligent Technical Systems. SASO Workshops 2014: 150-159 - 2013
- [j23]Tobias Reitmaier, Bernhard Sick:
Let us know your decision: Pool-based active training of a generative classifier with the selection strategy 4DS. Inf. Sci. 230: 106-131 (2013) - [j22]Paul Kaufmann, Kyrre Glette, Thiemo Gruber, Marco Platzner, Jim Tørresen, Bernhard Sick:
Classification of Electromyographic Signals: Comparing Evolvable Hardware to Conventional Classifiers. IEEE Trans. Evol. Comput. 17(1): 46-63 (2013) - [c38]Jörg Hähner, Stefan Rudolph, Sven Tomforde, Dominik Fisch, Bernhard Sick, Nils Kopal, Arno Wacker:
A Concept for Securing Cyber-Physical Systems with Organic Computing Techniques. ARCS Workshops 2013 - [c37]Andre Gensler, Thiemo Gruber, Bernhard Sick:
Blazing Fast Time Series Segmentation Based on Update Techniques for Polynomial Approximations. ICDM Workshops 2013: 1002-1011 - [e2]Hana Kubátová, Christian Hochberger, Martin Danek, Bernhard Sick:
Architecture of Computing Systems - ARCS 2013 - 26th International Conference, Prague, Czech Republic, February 19-22, 2013. Proceedings. Lecture Notes in Computer Science 7767, Springer 2013, ISBN 978-3-642-36423-5 [contents] - 2012
- [j21]Dominik Fisch, Martin Jänicke, Edgar Kalkowski, Bernhard Sick:
Learning from others: Exchange of classification rules in intelligent distributed systems. Artif. Intell. 187: 90-114 (2012) - [j20]Thiemo Gruber, Britta Meixner, Johann Prosser, Bernhard Sick:
Handedness tests for preschool children: A novel approach based on graphics tablets and support vector machines. Appl. Soft Comput. 12(4): 1390-1398 (2012) - [j19]Dominik Fisch, Martin Jänicke, Edgar Kalkowski, Bernhard Sick:
Techniques for knowledge acquisition in dynamically changing environments. ACM Trans. Auton. Adapt. Syst. 7(1): 16:1-16:25 (2012) - [c36]Mark J. Embrechts, Christopher J. Gatti, Jonathan D. Linton, Thiemo Gruber, Bernhard Sick:
Forecasting exchange rates with ensemble neural networks and ensemble K-PLS: A case study for the US Dollar per Indian Rupee. IJCNN 2012: 1-8 - [i1]Daniel Andrade, Bernhard Sick:
Lower Bound Bayesian Networks - An Efficient Inference of Lower Bounds on Probability Distributions in Bayesian Networks. CoRR abs/1205.2665 (2012) - 2011
- [j18]Alexander Hofmann, Bernhard Sick:
Online Intrusion Alert Aggregation with Generative Data Stream Modeling. IEEE Trans. Dependable Secur. Comput. 8(2): 282-294 (2011) - [j17]Dominik Fisch, Thiemo Gruber, Bernhard Sick:
SwiftRule: Mining Comprehensible Classification Rules for Time Series Analysis. IEEE Trans. Knowl. Data Eng. 23(5): 774-787 (2011) - [c35]Tobias Reitmaier, Bernhard Sick:
Active classifier training with the 3DS strategy. CIDM 2011: 88-95 - [c34]Dominik Fisch, Edgar Kalkowski, Bernhard Sick, Seppo J. Ovaska:
In Your Interest - Objective Interestingness Measures for a Generative Classifier. ICAART (1) 2011: 414-423 - [p5]Dominik Fisch, Martin Jänicke, Christian Müller-Schloer, Bernhard Sick:
Divergence Measures as a Generalised Approach to Quantitative Emergence. Organic Computing 2011: 53-66 - [p4]Dominik Fisch, Edgar Kalkowski, Bernhard Sick:
Collaborative Learning by Knowledge Exchange. Organic Computing 2011: 267-280 - 2010
- [j16]Erich Fuchs, Thiemo Gruber, Helmuth Pree, Bernhard Sick:
Temporal data mining using shape space representations of time series. Neurocomputing 74(1-3): 379-393 (2010) - [j15]Dominik Fisch, Alexander Hofmann, Bernhard Sick:
On the versatility of radial basis function neural networks: A case study in the field of intrusion detection. Inf. Sci. 180(12): 2421-2439 (2010) - [j14]Dominik Fisch, Bernhard Kühbeck, Bernhard Sick, Seppo J. Ovaska:
So near and yet so far: New insight into properties of some well-known classifier paradigms. Inf. Sci. 180(18): 3381-3401 (2010) - [j13]Erich Fuchs, Thiemo Gruber, Jiri Nitschke, Bernhard Sick:
Online Segmentation of Time Series Based on Polynomial Least-Squares Approximations. IEEE Trans. Pattern Anal. Mach. Intell. 32(12): 2232-2245 (2010) - [j12]Christian Gruber, Thiemo Gruber, Sebastian Krinninger, Bernhard Sick:
Online Signature Verification With Support Vector Machines Based on LCSS Kernel Functions. IEEE Trans. Syst. Man Cybern. Part B 40(4): 1088-1100 (2010) - [c33]Dominik Fisch, Ferdinand Kastl, Bernhard Sick:
Novelty-Aware Attack Recognition - Intrusion Detection with Organic Computing Techniques. DIPES/BICC 2010: 242-253 - [c32]Ulf Blanke, Bernt Schiele, Matthias Kreil, Paul Lukowicz, Bernhard Sick, Thiemo Gruber:
All for one or one for all? Combining heterogeneous features for activity spotting. PerCom Workshops 2010: 18-24 - [c31]Dominik Fisch, Martin Jänicke, Bernhard Sick, Christian Müller-Schloer:
Quantitative Emergence -- A Refined Approach Based on Divergence Measures. SASO 2010: 94-103
2000 – 2009
- 2009
- [j11]Markus Bauer, Oliver Buchtala, Timo Horeis, Ralf Kern, Bernhard Sick, Robert Wagner:
Technical data mining with evolutionary radial basis function classifiers. Appl. Soft Comput. 9(2): 765-774 (2009) - [j10]Seppo J. Ovaska, Bernhard Sick, Alden H. Wright:
Periodical switching between related goals for improving evolvability to a fixed goal in multi-objective problems. Inf. Sci. 179(23): 4046-4056 (2009) - [j9]Erich Fuchs, Thiemo Gruber, Jiri Nitschke, Bernhard Sick:
On-line motif detection in time series with SwiftMotif. Pattern Recognit. 42(11): 3015-3031 (2009) - [j8]Erich Fuchs, Christian Gruber, Tobias Reitmaier, Bernhard Sick:
Processing Short-Term and Long-Term Information With a Combination of Polynomial Approximation Techniques and Time-Delay Neural Networks. IEEE Trans. Neural Networks 20(9): 1450-1462 (2009) - [c30]Dominik Fisch, Martin Jänicke, Edgar Kalkowski, Bernhard Sick:
Learning by Teaching versus Learning by Doing: Knowledge Exchange in Organic Agent Systems. IEEE IA 2009: 31-38 - [c29]Dominik Fisch, Bernhard Sick:
Training of radial basis function classifiers with resilient propagation and variational Bayesian inference. IJCNN 2009: 838-847 - [c28]Tilmann Rabl, Andreas Lang, Thomas Hackl, Bernhard Sick, Harald Kosch:
Generating Shifting Workloads to Benchmark Adaptability in Relational Database Systems. TPCTC 2009: 116-131 - [c27]Daniel Andrade, Bernhard Sick:
Lower Bound Bayesian Networks - An Efficient Inference of Lower Bounds on Probability Distributions in Bayesian Networks. UAI 2009: 10-18 - 2008
- [j7]Werner Grass, Bernhard Sick, Theo Ungerer, Klaus Waldschmidt:
Selected papers of the ARCS06 conference: an introduction. Pers. Ubiquitous Comput. 12(2): 95-96 (2008) - [c26]Kyrre Glette, Jim Tørresen, Thiemo Gruber, Bernhard Sick, Paul Kaufmann, Marco Platzner:
Comparing Evolvable Hardware to Conventional Classifiers for Electromyographic Prosthetic Hand Control. AHS 2008: 32-39 - [p3]Christian Müller-Schloer, Bernhard Sick:
Controlled Emergence and Self-Organization. Organic Computing 2008: 81-103 - 2007
- [j6]Klaus Waldschmidt, Jan Haase, Werner Grass, Bernhard Sick:
Editorial. J. Syst. Archit. 53(5-6): 251-252 (2007) - [j5]Bernhard Sick, Seppo J. Ovaska:
Fusion of soft and hard computing: multi-dimensional categorization of computationally intelligent hybrid systems. Neural Comput. Appl. 16(2): 125-137 (2007) - [c25]Oliver Buchtala, Bernhard Sick:
Functional Knowledge Exchange Within an Intelligent Distributed System. ARCS 2007: 126-141 - [c24]Matthias Dose, Christian Gruber, Ariane Grunz, Christian Hook, Jürgen Kempf, Georg Scharfenberg, Bernhard Sick:
Towards an Automated Analysis of Neuroleptics' Impact on Human Hand Motor Skills. CIBCB 2007: 494-501 - [c23]Thomas Schon, Bernhard Sick, Markus Strassberger:
Hazard Situation Prediction Using Spatially and Temporally Distributed Vehicle Sensor Information. CIDM 2007: 261-268 - [c22]Timo Horeis, Bernhard Sick:
Collaborative Knowledge Discovery & Data Mining: From Knowledge to Experience. CIDM 2007: 421-428 - [c21]Oliver Buchtala, Bernhard Sick:
Goodness of Fit: Measures for a Fuzzy Classifier. FOCI 2007: 201-207 - [c20]Oliver Buchtala, Bernhard Sick:
Basic Technologies for Knowledge Transfer in Intelligent Systems. ALIFE 2007: 251-258 - [c19]Alexander Hofmann, Ivan Dedinski, Bernhard Sick, Hermann de Meer:
A Novelty-Driven Approach to Intrusion Alert Correlation Based on Distributed Hash Tables. ISCC 2007: 71-78 - [c18]Ivan Dedinski, Andreas Berl, Alexander Hofmann, Sebastian Heglmeier, Bernhard Sick, Hermann de Meer:
A Source Routing Solution to Non-Transitive Connectivity Problems in Distributed Hash Tables. ISCC 2007: 601-608 - [c17]Ivan Dedinski, Alexander Hofmann, Bernhard Sick:
Cooperative Keep-Alives: An Efficient Outage Detection Algorithm for P2P Overlay Networks. Peer-to-Peer Computing 2007: 140-150 - 2006
- [c16]Christian Müller-Schloer, Bernhard Sick:
Emergence in Organic Computing Systems: Discussion of a Controversial Concept. ATC 2006: 1-16 - [c15]Christian Gruber, Thiemo Gruber, Bernhard Sick:
Online Signature Verification with New Time Series Kernels for Support Vector Machines. ICB 2006: 500-508 - [e1]Werner Grass, Bernhard Sick, Klaus Waldschmidt:
Architecture of Computing Systems - ARCS 2006, 19th International Conference, Frankfurt/Main, Germany, March 13-16, 2006, Proceedings. Lecture Notes in Computer Science 3894, Springer 2006, ISBN 3-540-32765-7 [contents] - 2005
- [j4]Oliver Buchtala, Manuel Klimek, Bernhard Sick:
Evolutionary optimization of radial basis function classifiers for data mining applications. IEEE Trans. Syst. Man Cybern. Part B 35(5): 928-947 (2005) - 2004
- [p2]Bernhard Sick:
Indirect On-Line Tool Wear Monitoring. Computationally Intelligent Hybrid Systems 2004: 169-198 - 2003
- [c14]Oliver Buchtala, Alexander Hofmann, Bernhard Sick:
Fast and Efficient Training of RBF Networks. ICANN 2003: 43-51 - [c13]Peter Neumann, Bernhard Sick, Dirk Arndt, Wendy Gersten:
Evolutionary Optimisation of RBF Network Architectures in a Direct Marketing Application. ICANN 2003: 307-315 - [c12]Alexander Hofmann, Carsten Schmitz, Bernhard Sick:
Intrusion Detection in Computer Networks with Neural and Fuzzy Classifiers. ICANN 2003: 316-324 - [c11]Christian Gruber, Bernhard Sick:
Processing short-term and long-term information with a combination of hardand soft-computing techniques. SMC 2003: 126-133 - [c10]Alexander Hofmann, Carsten Schmitz, Bernhard Sick:
Rule extraction from neural networks for intrusion detection in computer networks. SMC 2003: 1259-1265 - [c9]Claudia Bach, Stefan Bredl, Wolfgang Kossa, Bernhard Sick:
Calibration of self-organizing maps for classification tasks. SMC 2003: 2877-2882 - [c8]Manuel Klimek, Bernhard Sick:
Architecture optimization of radial basis function networks with a combination of hard- and soft-computing techniques. SMC 2003: 4664-4671 - 2002
- [j3]Bernhard Sick:
Fusion of hard and soft computing techniques in indirect, online tool wear monitoring. IEEE Trans. Syst. Man Cybern. Part C 32(2): 80-91 (2002) - [c7]Walter Maydl, Bernhard Sick, Werner Grass:
Towards a Specification Technique for Component-Based Measurement and Control Software for Embedded Systems. EUROMICRO 2002: 74-80 - 2000
- [c6]Walter Maydl, Bernhard Sick:
Recurrent and Non-Recurrent Dynamic Network Paradigms: A Case Study. IJCNN (6) 2000: 73-80
1990 – 1999
- 1999
- [b1]Bernhard Sick:
Signalinterpretation mit neuronalen Netzen unter Nutzung von modellbasiertem Nebenwissen am Beispiel der Verschleißüberwachung von Werkzeugen in CNC-Drehmaschinen. Universität Passau, 1999, pp. I-X, 1-340 - [j2]Bernhard Sick, Werner Grass, Klaus Donner:
Multisensorfusion bei der Verarbeitung mikrosystembasierter Signale. Informationstechnik Tech. Inform. 41(4): 14-19 (1999) - [p1]Bernhard Sick:
Signalinterpretation mit Neuronalen Netzen unter Nutzung von modellbasiertem Nebenwissen am Beispiel der Verschleißüberwachung von Werkzeugen in CNC-Drehmaschinen. Ausgezeichnete Informatikdissertationen 1999: 223-232 - 1998
- [j1]Bernhard Sick:
On-line tool wear monitoring in turning using neural networks. Neural Comput. Appl. 7(4): 356-366 (1998) - [c5]Bernhard Sick:
Online tool wear monitoring in turning using time-delay neural networks. ICASSP 1998: 445-448 - [c4]Andreas Sicheneder, Armin Bender, Erich Fuchs, Roland Mandl, Bernhard Sick:
A framework for the graphical specification and execution of complex signal processing applications. ICASSP 1998: 1757-1760 - 1997
- [c3]Bernhard Sick:
Classifying the Wear of Turning Tools with Neural Networks. ICANN 1997: 1059-1064 - [c2]Martin Grajcar, Bernhard Sick:
The FFT butterfly operation in 4 processor cycles on a 24 bit fixed-point DSP with a pipelined multiplier. ICASSP 1997: 611-614 - [c1]Bernhard Sick:
Monitoring the wear of cutting tools in CNC-lathes with artificial neural networks. ICASSP 1997: 3381-3384
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-11-20 22:00 CET by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
