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ORCID9th ANNPR 2020: Winterthur, Switzerland
- Frank-Peter Schilling
, Thilo Stadelmann:
Artificial Neural Networks in Pattern Recognition - 9th IAPR TC3 Workshop, ANNPR 2020, Winterthur, Switzerland, September 2-4, 2020, Proceedings. Lecture Notes in Computer Science 12294, Springer 2020, ISBN 978-3-030-58308-8
Invited Papers
- Pascal Paysan, Igor Peterlík, Toon Roggen, Liangjia Zhu, Claas Wessels, Jan Schreier, Martin Buchacek, Stefan Scheib:
Deep Learning Methods for Image Guidance in Radiation Therapy. 3-22 - Nikolaus Korfhage, Markus Mühling, Bernd Freisleben:
Intentional Image Similarity Search. 23-35
Foundations
- Graham Spinks, Marie-Francine Moens:
Structured (De)composable Representations Trained with Neural Networks. 39-51 - Jeremy Gordon, David Rawlinson, Subutai Ahmad:
Long Distance Relationships Without Time Travel: Boosting the Performance of a Sparse Predictive Autoencoder in Sequence Modeling. 52-64 - Poonam Rajput, Sparsh Mittal, Sarthak Narayan:
Improving Accuracy and Efficiency of Object Detection Algorithms Using Multiscale Feature Aggregation Plugins. 65-76 - Christoph Walter Senn, Itsuo Kumazawa:
Abstract Echo State Networks. 77-88 - Shigeo Abe:
Minimal Complexity Support Vector Machines. 89-101 - Ahmad Aghaebrahimian, Mark Cieliebak:
Named Entity Disambiguation at Scale. 102-110
Applications
- Albert Matveev, Alexey Artemov, Denis Zorin, Evgeny Burnaev:
Geometric Attention for Prediction of Differential Properties in 3D Point Clouds. 113-124 - Stefan Glüge, Mohammadreza Amirian, Dandolo Flumini, Thilo Stadelmann:
How (Not) to Measure Bias in Face Recognition Networks. 125-137 - Tobias Ricken, Adrian Steinert, Peter Bellmann, Steffen Walter, Friedhelm Schwenker:
Feature Extraction: A Time Window Analysis Based on the X-ITE Pain Database. 138-148 - Peter Bellmann, Patrick Thiam, Friedhelm Schwenker:
Pain Intensity Recognition - An Analysis of Short-Time Sequences in a Real-World Scenario. 149-161 - Sina Famouri, Lia Morra, Fabrizio Lamberti:
A Deep Learning Approach for Efficient Registration of Dual View Mammography. 162-172 - Srinath Jayachandran, Ashlin Ghosh:
Deep Transfer Learning for Texture Classification in Colorectal Cancer Histology. 173-186 - Fabian Furger, Ludovic Amruthalingam, Alexander A. Navarini, Marc Pouly:
Applications of Generative Adversarial Networks to Dermatologic Imaging. 187-199 - Moritz Kaufmann, Martin Schüle, Theo H. M. Smits, Joël F. Pothier:
Typing Plasmids with Distributed Sequence Representation. 200-210 - Nouredine Hussain, Christopher Finelli:
KP-YOLO: A Modification of YOLO Algorithm for the Keypoint-Based Detection of QR Codes. 211-222 - Jasmin Dalferth, Sven Winkelmann, Friedhelm Schwenker:
Using Mask R-CNN for Image-Based Wear Classification of Solid Carbide Milling and Drilling Tools. 223-234 - Gregory Gygax, Martin Schüle:
A Hybrid Deep Learning Approach for Forecasting Air Temperature. 235-246 - Beat Wolf, Jonathan Donzallaz, Colette Jost, Amanda Hayoz, Stéphane Commend, Jean Hennebert, Pierre Kuonen:
Using CNNs to Optimize Numerical Simulations in Geotechnical Engineering. 247-256 - Anna Wróbel, Gregory Gygax, Andi Schmid, Thomas Ott:
Going for 2D or 3D? Investigating Various Machine Learning Approaches for Peach Variety Identification. 257-265 - Fady K. Fahmy, Mahmoud I. Khalil, Hazem M. Abbas:
A Transfer Learning End-to-End Arabic Text-To-Speech (TTS) Deep Architecture. 266-277 - Dalila Hattab:
ML-Based Trading Models: An Investigation During COVID-19 Pandemic Crisis. 278-290 - Fabio Garcea, Sina Famouri, Davide Valentino, Lia Morra, Fabrizio Lamberti:
iNNvestigate-GUI - Explaining Neural Networks Through an Interactive Visualization Tool. 291-303
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