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ORCIDMark B. Sandler
Mark Sandler 0001
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- affiliation: Queen Mary University of London, UK
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- Mark Sandler 0002
![[0000-0003-0352-6051]](https://dblp.uni-trier.de./img/orcid-mark.12x12.png "0000-0003-0352-6051")
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2020 – today
- 2024
[i34]Rodrigo Diaz, Carlos De La Vega Martin, Mark B. Sandler:
Towards Efficient Modelling of String Dynamics: A Comparison of State Space and Koopman based Deep Learning Methods. CoRR abs/2408.16650 (2024)- 2023
- [c156]Franco Caspe, Andrew P. McPherson, Mark B. Sandler:
FM Tone Transfer with Envelope Learning. Audio Mostly Conference 2023: 116-123 - [c155]Rodrigo Diaz, Ben Hayes, Charalampos Saitis, György Fazekas, Mark B. Sandler:
Rigid-Body Sound Synthesis with Differentiable Modal Resonators. ICASSP 2023: 1-5 - [c154]Jeff Miller, Johan Pauwels, Mark Sandler:
Polar Manhattan Displacement: Measuring Tonal Distances Between Chords Based on Intervallic Content. ISMIR 2023: 868-874 - [c153]Rodrigo Diaz, Charalampos Saitis, Mark B. Sandler:
Interactive Neural Resonators. NIME 2023 - [c152]Saurjya Sarkar, Louise Thorpe, Emmanouil Benetos, Mark Sandler:
Leveraging Synthetic Data for Improving Chamber Ensemble Separation. WASPAA 2023: 1-5 - [e1]Augusto Sarti, Fabio Antonacci, Mark Sandler, Paolo Bestagini, Simon Dixon, Beici Liang, Gaël Richard, Johan Pauwels:
Proceedings of the 24th International Society for Music Information Retrieval Conference, ISMIR 2023, Milan, Italy, November 5-9, 2023. 2023, ISBN 978-1-7327299-3-3 [contents] - [i33]Rodrigo Diaz, Charalampos Saitis, Mark Sandler:
Interactive Neural Resonators. CoRR abs/2305.14867 (2023) - [i32]Jordie Shier, Franco Caspe, Andrew Robertson, Mark Sandler, Charalampos Saitis, Andrew P. McPherson:
Differentiable Modelling of Percussive Audio with Transient and Spectral Synthesis. CoRR abs/2309.06649 (2023) - [i31]Franco Caspe, Andrew P. McPherson, Mark Sandler:
FM Tone Transfer with Envelope Learning. CoRR abs/2310.04811 (2023) - 2022
- [c151]Yudong Zhao, György Fazekas, Mark Sandler:
Transfer Learning for Violinist Identification. EUSIPCO 2022: 239-243 - [c150]Jeff Miller, Ken O'Hanlon, Mark B. Sandler:
Improving Balance in Automatic Chord Recognition with Random Forests. EUSIPCO 2022: 244-248 - [c149]Yudong Zhao, György Fazekas, Mark B. Sandler:
Violinist Identification Using Note-Level Timbre Feature Distributions. ICASSP 2022: 601-605 - [c148]Franco Caspe, Andrew McPherson, Mark Sandler:
DDX7: Differentiable FM Synthesis of Musical Instrument Sounds. ISMIR 2022: 608-616 - [c147]Saurjya Sarkar, Emmanouil Benetos, Mark Sandler:
EnsembleSet: a new high quality synthesised dataset for chamber ensemble separation. ISMIR 2022: 625-632 - [d2]Saurjya Sarkar, Emmanouil Benetos, Mark Sandler:
EnsembleSet. Zenodo, 2022
- [i30]Alejandro Delgado, Emir Demirel, Vinod Subramanian, Charalampos Saitis, Mark B. Sandler:
Deep Embeddings for Robust User-Based Amateur Vocal Percussion Classification. CoRR abs/2204.04646 (2022) - [i29]Alejandro Delgado, Charalampos Saitis, Emmanouil Benetos, Mark B. Sandler:
Deep Conditional Representation Learning for Drum Sample Retrieval by Vocalisation. CoRR abs/2204.04651 (2022) - [i28]Vinod Subramanian, Siddharth Gururani, Emmanouil Benetos, Mark B. Sandler:
Anomalous behaviour in loss-gradient based interpretability methods. CoRR abs/2207.07769 (2022) - [i27]Franco Caspe, Andrew McPherson, Mark Sandler:
DDX7: Differentiable FM Synthesis of Musical Instrument Sounds. CoRR abs/2208.06169 (2022) - [i26]Rodrigo Diaz, Ben Hayes, Charalampos Saitis, György Fazekas, Mark Sandler:
Rigid-Body Sound Synthesis with Differentiable Modal Resonators. CoRR abs/2210.15306 (2022) - 2021
- [j51]Ken O'Hanlon, Mark B. Sandler:
FifthNet: Structured Compact Neural Networks for Automatic Chord Recognition. IEEE ACM Trans. Audio Speech Lang. Process. 29: 2671-2682 (2021) - [c146]Jeff Miller, Vincenzo Nicosia, Mark Sandler:
Discovering Common Practice: Using Graph Theory to Compare Harmonic Sequences in Musical Audio Collections. DLfM 2021: 93-97 - [c145]Yudong Zhao, Changhong Wang, György Fazekas, Emmanouil Benetos, Mark B. Sandler:
Violinist identification based on vibrato features. EUSIPCO 2021: 381-385 - [c144]Saurjya Sarkar, Emmanouil Benetos, Mark B. Sandler:
Vocal Harmony Separation Using Time-Domain Neural Networks. Interspeech 2021: 3515-3519 - [i25]Beici Liang, György Fazekas, Mark B. Sandler:
Transfer Learning for Piano Sustain-Pedal Detection. CoRR abs/2103.13219 (2021) - [i24]Alejandro Delgado, SKoT McDonald, Ning Xu, Charalampos Saitis, Mark B. Sandler:
Learning Models for Query by Vocal Percussion: A Comparative Study. CoRR abs/2110.09223 (2021) - 2020
- [j50]Cornelia Metzig, Matthew Gould, Roshan Noronha, Roshani Abbey, Mark Sandler, Caroline Colijn:
Classification of origin with feature selection and network construction for folk tunes. Pattern Recognit. Lett. 133: 356-364 (2020) - [j49]Panos Kudumakis, Thomas Wilmering, Mark B. Sandler, Víctor Rodríguez-Doncel, Laurent Boch, Jaime Delgado:
The Challenge: From MPEG Intellectual Property Rights Ontologies to Smart Contracts and Blockchains [Standards in a Nutshell]. IEEE Signal Process. Mag. 37(2): 89-95 (2020) - [j48]Florian Thalmann, Geraint A. Wiggins, Mark B. Sandler:
Representing Modifiable and Reusable Musical Content on the Web With Constrained Multi-Hierarchical Structures. IEEE Trans. Multim. 22(10): 2645-2658 (2020) - [c143]Vinod Subramanian, Arjun Pankajakshan, Emmanouil Benetos, Ning Xu, SKoT McDonald, Mark B. Sandler:
A Study on the Transferability of Adversarial Attacks in Sound Event Classification. ICASSP 2020: 301-305 - [c142]Ken O'Hanlon, Mark B. Sandler:
The Fifthnet Chroma Extractor. ICASSP 2020: 3752-3756 - [c141]Fred Bruford, Olivier Lartillot, SKoT McDonald, Mark B. Sandler:
Multidimensional similarity modelling of complex drum loops using the GrooveToolbox. ISMIR 2020: 263-270 - [c140]Florian Thalmann, Kazuyoshi Yoshii, Thomas Wilmering, Geraint A. Wiggins, Mark B. Sandler:
A Method for Analysis of Shared Structure in Large Music Collections using Techniques from Genetic Sequencing and Graph Theory. ISMIR 2020: 343-350 - [i23]Johan Pauwels, György Fazekas, Mark B. Sandler:
A Critical Look at the Applicability of Markov Logic Networks for Music Signal Analysis. CoRR abs/2001.06086 (2020)
2010 – 2019
- 2019
- [c139]Alejandro Delgado, SKoT McDonald, Ning Xu, Mark B. Sandler:
A New Dataset for Amateur Vocal Percussion Analysis. Audio Mostly Conference 2019: 17-23 - [c138]Fred Bruford, Mathieu Barthet, SKoT McDonald, Mark B. Sandler:
Modelling Musical Similarity for Drum Patterns: A Perceptual Evaluation. Audio Mostly Conference 2019: 131-138 - [c137]Dalia Senvaityte, Johan Pauwels, Mark B. Sandler:
Guitar String Separation Using Non-Negative Matrix Factorization and Factor Deconvolution. Audio Mostly Conference 2019: 239-243 - [c136]Vinod Subramanian, Emmanouil Benetos, Mark B. Sandler:
Robustness of Adversarial Attacks in Sound Event Classification. DCASE 2019: 239-243 - [c135]Delia Fano Yela, Dan Stowell, Mark B. Sandler:
Spectral Visibility Graphs: Application to Similarity of Harmonic Signals. EUSIPCO 2019: 1-5 - [c134]Beici Liang, György Fazekas, Mark B. Sandler:
Piano Sustain-pedal Detection Using Convolutional Neural Networks. ICASSP 2019: 241-245 - [c133]Ken O'Hanlon, Mark B. Sandler:
Comparing CQT and Reassignment Based Chroma Features for Template-based Automatic Chord Recognition. ICASSP 2019: 860-864 - [c132]Beici Liang, György Fazekas, Mark B. Sandler:
Transfer Learning for Piano Sustain-Pedal Detection. IJCNN 2019: 1-6 - [c131]Johan Pauwels, Ken O'Hanlon, Emilia Gómez, Mark B. Sandler:
20 Years of Automatic Chord Recognition from Audio. ISMIR 2019: 54-63 - [c130]Fred Bruford, Mathieu Barthet, SKoT McDonald, Mark B. Sandler:
Groove Explorer: An Intelligent Visual Interface for Drum Loop Library Navigation. IUI Workshops 2019 - [c129]Johan Pauwels, Mark B. Sandler:
A Web-Based System For Suggesting New Practice Material To Music Learners Based On Chord Content. IUI Workshops 2019 - [c128]Panos Kudumakis, Thomas Wilmering, Mark B. Sandler, Jeremy D. Foss:
MPEG Intellectual Property Rights Ontologies for Media Trading and Personalization. DataTV@TVX 2019 - [i22]Delia Fano Yela, Dan Stowell, Mark B. Sandler:
Visibility graphs for robust harmonic similarity measures between audio spectra. CoRR abs/1903.01976 (2019) - [i21]Delia Fano Yela, Florian Thalmann, Vincenzo Nicosia, Dan Stowell, Mark B. Sandler:
Efficient On-line Computation of Visibility Graphs. CoRR abs/1905.03204 (2019) - [i20]Vinod Subramanian, Emmanouil Benetos, Ning Xu, SKoT McDonald, Mark B. Sandler:
Adversarial Attacks in Sound Event Classification. CoRR abs/1907.02477 (2019) - 2018
- [j47]Keunwoo Choi, György Fazekas, Kyunghyun Cho, Mark B. Sandler:
The Effects of Noisy Labels on Deep Convolutional Neural Networks for Music Tagging. IEEE Trans. Emerg. Top. Comput. Intell. 2(2): 139-149 (2018) - [c127]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
A Comparison of Audio Signal Preprocessing Methods for Deep Neural Networks on Music Tagging. EUSIPCO 2018: 1870-1874 - [c126]Beici Liang, György Fazekas, Mark B. Sandler:
Piano Legato-Pedal Onset Detection Based on a Sympathetic Resonance Measure. EUSIPCO 2018: 2484-2488 - [c125]Delia Fano Yela, Dan Stowell, Mark B. Sandler:
Does k Matter? k-NN Hubness Analysis for Kernel Additive Modelling Vocal Separation. LVA/ICA 2018: 280-289 - [c124]Adib Mehrabi, Keunwoo Choi, Simon Dixon, Mark B. Sandler:
Similarity Measures for Vocal-Based Drum Sample Retrieval Using Deep Convolutional Auto-Encoders. ICASSP 2018: 356-360 - [c123]Ken O'Hanlon, Mark B. Sandler:
Improved Detection of Semi-Percussive Onsets in Audio Using Temporal Reassignment. ICASSP 2018: 611-615 - [c122]Delia Fano Yela, Sebastian Ewert, Ken O'Hanlon, Mark B. Sandler:
Shift-Invariant Kernel Additive Modelling for Audio Source Separation. ICASSP 2018: 616-620 - [c121]Florian Thalmann, Thomas Wilmering, Mark B. Sandler:
Cultural Heritage Documentation and Exploration of Live Music Events with Linked Data. SAAM@ISWC 2018: 1-5 - [c120]Thomas Wilmering, Florian Thalmann, Mark B. Sandler:
Exploration of Grateful Dead Concerts and Memorabilia on the Semantic Web. ISWC (P&D/Industry/BlueSky) 2018 - [c119]Alo Allik, Florian Thalmann, Mark B. Sandler:
MusicLynx: Exploring Music Through Artist Similarity Graphs. WWW (Companion Volume) 2018: 167-170 - [i19]Adib Mehrabi, Keunwoo Choi, Simon Dixon, Mark B. Sandler:
Similarity measures for vocal-based drum sample retrieval using deep convolutional auto-encoders. CoRR abs/1802.05178 (2018) - [i18]Delia Fano Yela, Dan Stowell, Mark B. Sandler:
Does k Matter? k-NN Hubness Analysis for Kernel Additive Modelling Vocal Separation. CoRR abs/1804.02325 (2018) - 2017
- [j46]Mi Tian, Mark B. Sandler:
Towards Music Structural Segmentation across Genres: Features, Structural Hypotheses, and Annotation Principles. ACM Trans. Intell. Syst. Technol. 8(2): 23:1-23:19 (2017) - [c118]Beici Liang, György Fazekas, Mark B. Sandler:
Recognition of Piano Pedalling Techniques Using Gesture Data. Audio Mostly Conference 2017: 9:1-9:5 - [c117]Angela McArthur, Mark Sandler, Rebecca Stewart:
Distance in audio for VR: constraints and opportunities. Audio Mostly Conference 2017: 28:1-28:7 - [c116]Ben White, Adib Mehrabi, Mark B. Sandler:
An Archival Echo: Recalling the public domain through real-time query by vocalisation. Audio Mostly Conference 2017: 42:1-42:4 - [c115]Elio Quinton, Ken O'Hanlon, Simon Dixon, Mark B. Sandler:
Tracking metrical structure changes with sparse-NMF. ICASSP 2017: 41-45 - [c114]Delia Fano Yela, Sebastian Ewert, Derry FitzGerald, Mark B. Sandler:
Interference reduction in music recordings combining Kernel Additive Modelling and Non-Negative Matrix Factorization. ICASSP 2017: 51-55 - [c113]Ken O'Hanlon, Sebastian Ewert, Johan Pauwels, Mark B. Sandler:
Improved template based chord recognition using the CRP feature. ICASSP 2017: 306-310 - [c112]Sebastian Ewert, Mark B. Sandler:
Structured dropout for weak label and multi-instance learning and its application to score-informed source separation. ICASSP 2017: 2277-2281 - [c111]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Convolutional recurrent neural networks for music classification. ICASSP 2017: 2392-2396 - [c110]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Transfer Learning for Music Classification and Regression Tasks. ISMIR 2017: 141-149 - [c109]Johan Pauwels, Ken O'Hanlon, György Fazekas, Mark B. Sandler:
Confidence Measures and Their Applications in Music Labelling Systems Based on Hidden Markov Models. ISMIR 2017: 279-285 - [c108]Beici Liang, György Fazekas, Andrew P. McPherson, Mark B. Sandler:
Piano pedaller: a measurement system for classification and visualisation of piano pedalling techniques. NIME 2017: 325-329 - [c107]Delia Fano Yela, Sebastian Ewert, Derry Fitzgerald, Mark B. Sandler:
On the Importance of Temporal Context in Proximity Kernels: A Vocal Separation Case Study. Semantic Audio 2017 - [c106]Sebastian Ewert, Mark B. Sandler:
An augmented lagrangian method for piano transcription using equal loudness thresholding and lstm-based decoding. WASPAA 2017: 146-150 - [i17]Delia Fano Yela, Sebastian Ewert, Derry FitzGerald, Mark B. Sandler:
On the Importance of Temporal Context in Proximity Kernels: A Vocal Separation Case Study. CoRR abs/1702.02130 (2017) - [i16]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Transfer learning for music classification and regression tasks. CoRR abs/1703.09179 (2017) - [i15]Keunwoo Choi, György Fazekas, Kyunghyun Cho, Mark B. Sandler:
On the Robustness of Deep Convolutional Neural Networks for Music Classification. CoRR abs/1706.02361 (2017) - [i14]Sebastian Ewert, Mark B. Sandler:
An Augmented Lagrangian Method for Piano Transcription using Equal Loudness Thresholding and LSTM-based Decoding. CoRR abs/1707.00160 (2017) - [i13]Keunwoo Choi, György Fazekas, Kyunghyun Cho, Mark B. Sandler:
A Comparison on Audio Signal Preprocessing Methods for Deep Neural Networks on Music Tagging. CoRR abs/1709.01922 (2017) - [i12]Keunwoo Choi, György Fazekas, Kyunghyun Cho, Mark B. Sandler:
A Tutorial on Deep Learning for Music Information Retrieval. CoRR abs/1709.04396 (2017) - [i11]Delia Fano Yela, Sebastian Ewert, Ken O'Hanlon, Mark B. Sandler:
Shift-Invariant Kernel Additive Modelling for Audio Source Separation. CoRR abs/1711.00351 (2017) - 2016
- [j45]Pasi Saari, György Fazekas, Tuomas Eerola, Mathieu Barthet, Olivier Lartillot, Mark B. Sandler:
Genre-Adaptive Semantic Computing and Audio-Based Modelling for Music Mood Annotation. IEEE Trans. Affect. Comput. 7(2): 122-135 (2016) - [j44]Sebastian Ewert, Mark B. Sandler:
Piano Transcription in the Studio Using an Extensible Alternating Directions Framework. IEEE ACM Trans. Audio Speech Lang. Process. 24(11): 1983-1997 (2016) - [c105]Florian Thalmann, György Fazekas, Geraint A. Wiggins, Mark B. Sandler:
Creating, Visualizing, and Analyzing Dynamic Music Objects in the Browser with the Dymo Designer. Audio Mostly Conference 2016: 39-46 - [c104]Ken O'Hanlon, Mark B. Sandler:
Compositional chroma estimation using powered Euclidean distance. EUSIPCO 2016: 1237-1241 - [c103]Francisco J. Rodríguez-Serrano, Sebastian Ewert, Pedro Vera-Candeas, Mark B. Sandler:
A score-informed shift-invariant extension of complex matrix factorization for improving the separation of overlapped partials in music recordings. ICASSP 2016: 61-65 - [c102]Elio Quinton, Mark B. Sandler, Simon Dixon:
Estimation of the reliability of multiple rhythm features extraction from a single descriptor. ICASSP 2016: 256-260 - [c101]Ken O'Hanlon, Mark B. Sandler:
An iterative hard thresholding approach to ℓ0 sparse Hellinger NMF. ICASSP 2016: 4737-4741 - [c100]Sebastian Ewert, Siying Wang, Meinard Müller, Mark B. Sandler:
Score-Informed Identification of Missing and Extra Notes in Piano Recordings. ISMIR 2016: 30-36 - [c99]Alo Allik, György Fazekas, Mark B. Sandler:
An Ontology for Audio Features. ISMIR 2016: 73-79 - [c98]Michele Buccoli, Massimiliano Zanoni, György Fazekas, Augusto Sarti, Mark B. Sandler:
A Higher-Dimensional Expansion of Affective Norms for English Terms for Music Tagging. ISMIR 2016: 316-322 - [c97]Mi Tian, Mark B. Sandler:
Music Structural Segmentation Across Genres with Gammatone Features. ISMIR 2016: 561-567 - [c96]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Automatic Tagging Using Deep Convolutional Neural Networks. ISMIR 2016: 805-811 - [c95]Mariano Mora-Mcginity, Alo Allik, György Fazekas, Mark B. Sandler:
MusicWeb: Music Discovery with Open Linked Semantic Metadata. MTSR 2016: 291-296 - [c94]Florian Thalmann, Alfonso Pérez Carrillo, György Fazekas, Geraint A. Wiggins, Mark B. Sandler:
The Mobile Audio Ontology: Experiencing Dynamic Music Objects on Mobile Devices. ICSC 2016: 47-54 - [c93]Alo Allik, György Fazekas, Mark B. Sandler:
Ontological Representation of Audio Features. ISWC (2) 2016: 3-11 - [c92]Alo Allik, Mariano Mora-Mcginity, György Fazekas, Mark B. Sandler:
MusicWeb: Music Discovery with Open Linked Semantic Metadata. ISWC (Posters & Demos) 2016 - [c91]Thomas Wilmering, György Fazekas, Mark B. Sandler:
AUFX-O: Novel Methods for the Representation of Audio Processing Workflows. ISWC (2) 2016: 229-237 - [c90]Thomas Wilmering, Mark B. Sandler:
Interdisciplinary Classification of Audio Effects in the Audio Effect Ontology. ISWC (Posters & Demos) 2016 - [c89]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Towards Playlist Generation Algorithms Using RNNs Trained on Within-Track Transitions. UMAP (Extended Proceedings) 2016 - [i10]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Text-based LSTM networks for Automatic Music Composition. CoRR abs/1604.05358 (2016) - [i9]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Automatic tagging using deep convolutional neural networks. CoRR abs/1606.00298 (2016) - [i8]Sebastian Ewert, Mark B. Sandler:
Piano Transcription in the Studio Using an Extensible Alternating Directions Framework. CoRR abs/1606.00785 (2016) - [i7]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Towards Playlist Generation Algorithms Using RNNs Trained on Within-Track Transitions. CoRR abs/1606.02096 (2016) - [i6]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Explaining Deep Convolutional Neural Networks on Music Classification. CoRR abs/1607.02444 (2016) - [i5]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Towards Music Captioning: Generating Music Playlist Descriptions. CoRR abs/1608.04868 (2016) - [i4]Keunwoo Choi, György Fazekas, Mark B. Sandler, Kyunghyun Cho:
Convolutional Recurrent Neural Networks for Music Classification. CoRR abs/1609.04243 (2016) - [i3]Sebastian Ewert, Mark B. Sandler:
Structured Dropout for Weak Label and Multi-Instance Learning and Its Application to Score-Informed Source Separation. CoRR abs/1609.04557 (2016) - [i2]Delia Fano Yela, Sebastian Ewert, Derry FitzGerald, Mark B. Sandler:
Interference Reduction in Music Recordings Combining Kernel Additive Modelling and Non-Negative Matrix Factorization. CoRR abs/1609.06210 (2016) - 2015
- [c88]Mathieu Barthet, György Fazekas, Alo Allik, Mark B. Sandler:
Moodplay: an interactive mood-based musical experience. Audio Mostly Conference 2015: 3:1-3:8 - [c87]Mi Tian, György Fazekas, Dawn A. A. Black, Mark B. Sandler:
On the use of the tempogram to describe audio content and its application to Music structural segmentation. ICASSP 2015: 419-423 - [c86]Sebastian Ewert, Mark D. Plumbley, Mark B. Sandler:
A dynamic programming variant of non-negative matrix deconvolution for the transcription of struck string instruments. ICASSP 2015: 569-573 - [c85]Ken O'Hanlon, Mark B. Sandler, Mark D. Plumbley:
Non-negative matrix factorisation incorporating greedy hellinger sparse coding applied to polyphonic music transcription. ICASSP 2015: 2214-2218 - [i1]Keunwoo Choi, György Fazekas, Mark B. Sandler:
Understanding Music Playlists. CoRR abs/1511.07004 (2015) - 2014
- [j43]Panos Kudumakis, Mark B. Sandler, Angelos-Christos G. Anadiotis, Iakovos S. Venieris, Angelo Difino, Xin Wang, Giuseppe Tropea, Michael Grafl, Víctor Rodríguez-Doncel, Silvia Llorente, Jaime Delgado:
MPEG-M: A digital media ecosystem for interoperable applications. Signal Process. Image Commun. 29(1): 150-166 (2014) - [c84]Sebastian Ewert, Mark D. Plumbley, Mark B. Sandler:
Accounting for phase cancellations in non-negative matrix factorization using weighted distances. ICASSP 2014: 649-653 - [c83]Mi Tian, Ajay Srinivasamurthy, Mark B. Sandler, Xavier Serra:
A study of instrument-wise onset detection in Beijing Opera percussion ensembles. ICASSP 2014: 2159-2163 - [c82]Mi Tian, György Fazekas, Dawn A. A. Black, Mark B. Sandler:
Design And Evaluation of Onset Detectors using Different Fusion Policies. ISMIR 2014: 631-636 - [c81]Chris Baume, György Fazekas, Mathieu Barthet, David Marston, Mark B. Sandler:
Selection of Audio Features for Music Emotion Recognition Using Production Music. Semantic Audio 2014 - [c80]Carl Bussey, Michael Terrell, Raihan Rahman, Mark B. Sandler:
Metadata Features that Affect Artificial Reverberator Intensity. Semantic Audio 2014 - [c79]Rubén Jesús García, Costantino Taglialatela, Panos Kudumakis, Isabel Barbancho, Lorenzo J. Tardón, Mark B. Sandler:
Interactive Music Applications by MPEG-A Support in Sonic Visualizer. Semantic Audio 2014 - [c78]Steven Hargreaves, Geraint A. Wiggins, Mark B. Sandler:
A Semantic Web Approach to Pattern Discovery in Data and Music. Semantic Audio 2014 - [c77]Sefki Kolozali, György Fazekas, Mathieu Barthet, Mark B. Sandler:
A Framework for Automatic Ontology Generation Based on Semantic Audio Analysis. Semantic Audio 2014 - [c76]Ting Lou, Mathieu Barthet, György Fazekas, Mark B. Sandler:
Evaluation and Improvement of the Mood Conductor Interactive System. Semantic Audio 2014 - [d1]Mi Tian, Ajay Srinivasamurthy, Mark Sandler, Xavier Serra:
Beijing Opera Percussion Instrument Dataset. Zenodo, 2014 - 2013
- [j42]Xue Wen, Mark Sandler:
Fast Additive Sinusoidal Synthesis With a Subband Sinusoidal Method. IEEE Signal Process. Lett. 20(5): 467-470 (2013) - [j41]Sefki Kolozali, Mathieu Barthet, György Fazekas, Mark B. Sandler:
Automatic Ontology Generation for Musical Instruments Based on Audio Analysis. IEEE Trans. Speech Audio Process. 21(10): 2207-2220 (2013) - [c75]György Fazekas, Mathieu Barthet, Mark B. Sandler:
Mood Conductor: Emotion-Driven Interactive Music Performance. ACII 2013: 726 - [c74]György Fazekas, Mathieu Barthet, Mark B. Sandler:
Novel Methods in Facilitating Audience and Performer Interaction Using the Mood Conductor Framework. CMMR 2013: 122-147 - [c73]Mi Tian, György Fazekas, Dawn A. A. Black, Mark B. Sandler:
Towards the Representation of Chinese Traditional Music: A State of the Art Review of Music Metadata Standards. Dublin Core Conference 2013: 71-81 - [c72]Alo Allik, György Fazekas, Simon Dixon, Mark B. Sandler:
Facilitating Music Information Research with Shared Open Vocabularies. ESWC (Satellite Events) 2013: 178-183 - [c71]Alo Allik, György Fazekas, Simon Dixon, Mark B. Sandler:
A Shared Vocabulary for Audio Features. ESWC (Satellite Events) 2013: 285-286 - [c70]Sebastian Ewert, Meinard Müller, Mark B. Sandler:
Efficient data adaption for musical source separation methods based on parametric models. ICASSP 2013: 46-50 - [c69]György Fazekas, Mathieu Barthet, Mark B. Sandler:
Demo paper: The BBC Desktop Jukebox music recommendation system: A large scale trial with professional users. ICME Workshops 2013: 1-2 - [c68]Pasi Saari, Mathieu Barthet, György Fazekas, Tuomas Eerola, Mark B. Sandler:
Semantic models of musical mood: Comparison between crowd-sourced and curated editorial tags. ICME Workshops 2013: 1-6 - [c67]Pasi Saari, Tuomas Eerola, György Fazekas, Mathieu Barthet, Olivier Lartillot, Mark B. Sandler:
The Role of Audio and Tags in Music Mood Prediction: A Study Using Semantic Layer Projection. ISMIR 2013: 201-206 - [c66]Thomas Wilmering, György Fazekas, Mark B. Sandler:
The Audio Effects Ontology. ISMIR 2013: 215-220 - [c65]Katerina Kosta, Yading Song, György Fazekas, Mark B. Sandler:
A Study of Cultural Dependence of Perceived Mood in Greek Music. ISMIR 2013: 317-322 - [c64]Mathieu Barthet, David Marston, Chris Baume, György Fazekas, Mark B. Sandler:
Design and Evaluation of Semantic Mood Models for Music Recommendation using Editorial Tags. ISMIR 2013: 421-426 - [c63]György Fazekas, Mark B. Sandler:
Describing audio production workflows on the semantic web. WIAMIS 2013: 1-4 - 2012
- [j40]Michael Terrell, Mark B. Sandler:
An Offline, Automatic Mixing Method for Live Music, Incorporating Multiple Sources, Loudspeakers, and Room Effects. Comput. Music. J. 36(2): 37-54 (2012) - [j39]Steven Hargreaves, Anssi Klapuri, Mark B. Sandler:
Structural Segmentation of Multitrack Audio. IEEE Trans. Speech Audio Process. 20(10): 2637-2647 (2012) - [c62]Mathieu Barthet, György Fazekas, Mark B. Sandler:
Music Emotion Recognition: From Content- to Context-Based Models. CMMR 2012: 228-252 - [c61]Yves Raimond, Mark B. Sandler:
Evaluation of the Music Ontology Framework. ESWC 2012: 255-269 - 2011
- [j38]Inseon Jang, Panos Kudumakis, Mark B. Sandler, Kyeongok Kang:
The MPEG Interactive Music Application Format Standard [Standards in a Nutshell]. IEEE Signal Process. Mag. 28(1): 150-154 (2011) - [j37]Rebecca Stewart, Mark B. Sandler:
An Auditory Display in Playlist Generation. IEEE Signal Process. Mag. 28(4): 14-23 (2011) - [j36]Panos Kudumakis, Xin Wang, Sergio Matone, Mark B. Sandler:
MPEG-M: Multimedia Service Platform Technologies [Standards in a Nutshell]. IEEE Signal Process. Mag. 28(6): 159-163 (2011) - [j35]Benjamin Fields, Kurt Jacobson, Christophe Rhodes, Mark d'Inverno, Mark B. Sandler, Michael A. Casey:
Analysis and Exploitation of Musician Social Networks for Recommendation and Discovery. IEEE Trans. Multim. 13(4): 674-686 (2011) - [c60]Rebecca Stewart, Mark B. Sandler:
The amblr: A mobile spatial audio music browser. ICME 2011: 1-6 - [c59]Sefki Kolozali, Mathieu Barthet, György Fazekas, Mark B. Sandler:
Knowledge Representation Issues in Musical Instrument Ontology Design. ISMIR 2011: 465-470 - [c58]György Fazekas, Mark B. Sandler:
The Studio Ontology Framework. ISMIR 2011: 471-476 - [c57]György Fazekas, Thomas Wilmering, Mark B. Sandler:
A Knowledge Representation Framework for Context-Dependent Audio Processing. Semantic Audio 2011 - 2010
- [j34]Xue Wen, Mark Sandler:
On the Characterization of Slowly Varying Sinusoids. EURASIP J. Audio Speech Music. Process. 2010 (2010) - [c56]Rebecca Stewart, Panos Kudumakis, Mark B. Sandler:
Interactive Music Applications and Standards. CMMR 2010: 20-30 - [c55]Mathieu Barthet, Steven Hargreaves, Mark B. Sandler:
Speech/Music Discrimination in Audio Podcast Using Structural Segmentation and Timbre Recognition. CMMR 2010: 138-162 - [c54]Rebecca Stewart, Mark B. Sandler:
Database of omnidirectional and B-format room impulse responses. ICASSP 2010: 165-168 - [c53]Chris Cannam, Christian Landone, Mark B. Sandler:
Sonic visualiser: an open source application for viewing, analysing, and annotating music audio files. ACM Multimedia 2010: 1467-1468 - [c52]Sefki Kolozali, Mathieu Barthet, György Fazekas, Mark B. Sandler:
Towards the Automatic Generation of a Semantic Web Ontology for Musical Instruments. SAMT 2010: 186-187 - [c51]Thomas Wilmering, Mark B. Sandler:
RDFx: Audio Effects Utilising Musical Metadata. ICSC 2010: 452-453
2000 – 2009
- 2009
- [j33]Katy C. Noland, Mark B. Sandler:
Influences of Signal Processing, Tone Profiles, and Chord Progressions on a Model for Estimating the Musical Key from Audio. Comput. Music. J. 33(1): 42-56 (2009) - [j32]Yves Raimond, Christopher Sutton, Mark B. Sandler:
Interlinking Music-Related Data on the Web. IEEE Multim. 16(2): 52-63 (2009) - [j31]Mark Levy, Mark B. Sandler:
Music Information Retrieval Using Social Tags and Audio. IEEE Trans. Multim. 11(3): 383-395 (2009) - [c50]Wen Xue, Mark Sandler:
Additive and multiplicative reestimation schemes for the sinusoid modeling of audio. EUSIPCO 2009: 904-908 - [c49]Kurt Jacobson, Yves Raimond, Mark B. Sandler:
An Ecosystem for Transparent Music Similarity in an Open World. ISMIR 2009: 33-38 - [c48]Dan Tidhar, György Fazekas, Sefki Kolozali, Mark B. Sandler:
Publishing Music Similarity Features on the Semantic Web. ISMIR 2009: 447-452 - 2008
- [j30]Mark Levy, Mark B. Sandler:
Structural Segmentation of Musical Audio by Constrained Clustering. IEEE Trans. Speech Audio Process. 16(2): 318-326 (2008) - [j29]Joshua D. Reiss, Mark B. Sandler:
Detection and Removal of Limit Cycles in Sigma Delta Modulators. IEEE Trans. Circuits Syst. I Regul. Pap. 55-I(10): 3119-3130 (2008) - [c47]Kurt Jacobson, Mark B. Sandler:
Musically Meaningful or Just Noise? An Analysis of On-line Artist Networks. CMMR 2008: 107-118 - [c46]Ben Fields, Michael A. Casey, Kurt Jacobson, Mark B. Sandler:
Do You sound like your Friends? Exploring Artist Similarity via Artist Social Network Relationships and audio signal Processing. ICMC 2008 - [c45]Yves Raimond, Mark B. Sandler:
A Web of Musical Information. ISMIR 2008: 263-268 - [c44]Kurt Jacobson, Mark B. Sandler, Benjamin Fields:
Using Audio Analysis and Network Structure to Identify Communities in On-Line Social Networks of Artists. ISMIR 2008: 269-274 - [c43]Yves Raimond, Christopher Sutton, Mark B. Sandler:
Automatic Interlinking of Music Datasets on the Semantic Web. LDOW 2008 - 2007
- [j28]Xue Wen, Mark Sandler:
Calculation of radix-2 discrete multiresolution Fourier transform. Signal Process. 87(10): 2455-2460 (2007) - [j27]Emmanuel Ravelli, Juan Pablo Bello, Mark B. Sandler:
Automatic Rhythm Modification of Drum Loops. IEEE Signal Process. Lett. 14(4): 228-231 (2007) - [c42]Mark Levy, Katy C. Noland, Mark B. Sandler:
A Comparison of Timbral and Harmonic Music Segmentation Algorithms. ICASSP (4) 2007: 1433-1436 - [c41]Mark Levy, Mark B. Sandler:
A Semantic Space for Music Derived from Social Tags. ISMIR 2007: 411-416 - [c40]Yves Raimond, Samer A. Abdallah, Mark B. Sandler, Frederick Giasson:
The Music Ontology. ISMIR 2007: 417-422 - [c39]Yves Raimond, Christopher Sutton, Mark B. Sandler:
A distributed data space for music-related information. MS 2007: 81-89 - 2006
- [j26]Samer A. Abdallah, Mark B. Sandler, Christophe Rhodes, Michael A. Casey:
Using duration models to reduce fragmentation in audio segmentation. Mach. Learn. 65(2-3): 485-515 (2006) - [j25]Juan Pablo Bello, Laurent Daudet, Mark B. Sandler:
Automatic Piano Transcription Using Frequency and Time-Domain Information. IEEE Trans. Speech Audio Process. 14(6): 2242-2251 (2006) - [c38]Dawn A. A. Black, Mark B. Sandler:
A voicing decision driven forward error correction scheme for voice over IP applications. EUSIPCO 2006: 1-4 - [c37]Mark Levy, Mark B. Sandler:
New methods in structural segmentation of musical audio. EUSIPCO 2006: 1-5 - [c36]Andrew Nesbit, Mike E. Davies, Mark D. Plumbley, Mark B. Sandler:
Source extraction from two-channel mixtures by joint cosine packet analysis. EUSIPCO 2006: 1-5 - [c35]Mark Levy, Mark B. Sandler, Michael A. Casey:
Extraction of High-Level Musical Structure From Audio Data and Its Application to Thumbnail Generation. ICASSP (5) 2006: 13-16 - [c34]Nicolas Chetry, Mark B. Sandler:
Linear Predictive Models for Musical Instrument Identification. ICASSP (5) 2006: 225-228 - [c33]Juan Pablo Bello, Emmanuel Ravelli, Mark B. Sandler:
Drum Sound Analysis for the Manipulation of Rhythm in Drum Loops. ICASSP (5) 2006: 233-236 - [c32]Christophe Rhodes, Michael A. Casey, Samer A. Abdallah, Mark B. Sandler:
A Markov-Chain Monte-Carlo Approach to Musical Audio Segmentation. ICASSP (5) 2006: 797-800 - [c31]Katy C. Noland, Mark B. Sandler:
Key Estimation Using a Hidden Markov Model. ISMIR 2006: 121-126 - [c30]Chris Cannam, Christian Landone, Mark B. Sandler, Juan Pablo Bello:
The Sonic Visualiser: A Visualisation Platform for Semantic Descriptors from Musical Signals. ISMIR 2006: 324-327 - [c29]Yves Raimond, Samer A. Abdallah, Mark B. Sandler, Mounia Lalmas:
A Scalable Framework for Multimedia Knowledge Management. SAMT 2006: 11-25 - 2005
- [j24]Juan Pablo Bello, Laurent Daudet, Samer A. Abdallah, Chris Duxbury, Mike E. Davies, Mark B. Sandler:
A Tutorial on Onset Detection in Music Signals. IEEE Trans. Speech Audio Process. 13(5-2): 1035-1047 (2005) - [j23]Derk Reefman, Joshua D. Reiss, Erwin Janssen, Mark B. Sandler:
Description of limit cycles in sigma-delta modulators. IEEE Trans. Circuits Syst. I Regul. Pap. 52-I(6): 1211-1223 (2005) - [j22]Jean-Julien Aucouturier, François Pachet, Mark B. Sandler:
"The way it Sounds": timbre models for analysis and retrieval of music signals. IEEE Trans. Multim. 7(6): 1028-1035 (2005) - [c28]Christopher Harte, Mark B. Sandler, Samer A. Abdallah, Emilia Gómez:
Symbolic Representation of Musical Chords: A Proposed Syntax for Text Annotations. ISMIR 2005: 66-71 - [c27]Samer A. Abdallah, Katy C. Noland, Mark B. Sandler, Michael A. Casey, Christophe Rhodes:
Theory and Evaluation of a Bayesian Music Structure Extractor. ISMIR 2005: 420-425 - [c26]Wen Xue, Mark Sandler:
A Partial Searching Algorithm and Its Application for Polyphonic Music Transcription. ISMIR 2005: 690-695 - 2004
- [j21]Juan Pablo Bello, Chris Duxbury, Mike E. Davies, Mark B. Sandler:
On the use of phase and energy for musical onset detection in the complex domain. IEEE Signal Process. Lett. 11(6): 553-556 (2004) - [j20]Laurent Daudet, Mark B. Sandler:
MDCT analysis of sinusoids: exact results and applications to coding artifacts reduction. IEEE Trans. Speech Audio Process. 12(3): 302-312 (2004) - [c25]Chris Duxbury, Nicolas Chetry, Mark B. Sandler, Mike E. Davies:
An efficient two-stage implementation of harmonic matching pursuit. EUSIPCO 2004: 2271-2274 - [c24]Mark B. Sandler, Dawn A. A. Black:
Loss Resilient, Scalable Audio Compression and Streaming. EWIMT 2004 - [c23]Juan Pablo Bello, Mark B. Sandler:
Centre for Digital Music: Studio Report. ICMC 2004 - [c22]Josh Reiss, Mark B. Sandler:
Audio Issues In MIR Evaluation. ISMIR 2004 - 2003
- [c21]Juan Pablo Bello, Mark B. Sandler:
Phase-based note onset detection for music signals. ICASSP (5) 2003: 441-444 - 2002
- [j19]Mark D. Plumbley, Samer A. Abdallah, Juan Pablo Bello, Mike E. Davies, Giuliano Monti, Mark B. Sandler:
Automatic Music Transcription and Audio Source Separation. Cybern. Syst. 33(6): 603-627 (2002) - [c20]Laurent Daudet, Mark Sandler, Bruno Torrésani:
Audio representations on overcomplete sets. DSP 2002: 583-586 - [c19]Jeremy Pickens, Juan Pablo Bello, Tim Crawford, Matthew J. Dovey, Giuliano Monti, Mark B. Sandler:
Polyphonic Score Retrieval Using Polyphonic Audio Queries: A Harmonic Modeling Approach. ISMIR 2002 - 2000
- [j18]Gabriela Castellano, James F. Boyce, Mark B. Sandler:
Regularized CDWT optical flow applied to moving-target detection in IR imagery. Mach. Vis. Appl. 11(6): 277-288 (2000) - [c18]Christian Landone, Mark B. Sandler:
Applications of binaural processing to surround sound reproduction in large spaces. ISCAS 2000: 217-220 - [c17]Juan Pablo Bello, Giuliano Monti, Mark B. Sandler:
Techniques for Automatic Music Transcription. ISMIR 2000 - [c16]Daniel Bendor, Mark B. Sandler:
Time Domain Extraction of Vibrato from Monophonic Instruments. ISMIR 2000
1990 – 1999
- 1999
- [j17]R. Nawrocki, J. M. Goldberg, Mark B. Sandler:
Information-theoretic constraints on noise shaping networks with minimum noise power gain. Int. J. Circuit Theory Appl. 27(4): 437-441 (1999) - [c15]M. Price, Mark B. Sandler:
Investigation of a least squares method for high order filter synthesis. ISCAS (3) 1999: 315-318 - [c14]B. Leslie, Mark B. Sandler:
A wavelet packet algorithm for 1D data with no block end effects. ISCAS (3) 1999: 423-426 - 1998
- [c13]Tryphon Lambrou, Panos Kudumakis, Robert D. Speller, Mark B. Sandler, Alf D. Linney:
Classification of audio signals using statistical features on time and wavelet transform domains. ICASSP 1998: 3621-3624 - 1997
- [j16]Anthony Magrath, Mark B. Sandler:
A use of sigma-delta modulation in power digital-to-analogue conversion. Int. J. Circuit Theory Appl. 25(5): 439-455 (1997) - 1996
- [j15]Panos Kudumakis, Mark B. Sandler:
On the compression obtainable with four-tap wavelets. IEEE Signal Process. Lett. 3(8): 231-233 (1996) - 1995
- [c12]Panos Kudumakis, Mark B. Sandler:
On the performance of wavelets for low bit rate coding of audio signals. ICASSP 1995: 3087-3090 - [c11]Chris Dunn, Mark B. Sandler:
Linearising Sigma-Delta Modulators Using Dither and Chaos. ISCAS 1995: 625-628 - [c10]Simon M. Kershaw, Steve Summerfield, Mark B. Sandler:
On Sigma-Delta Signal Processing Remodulator Complexity. ISCAS 1995: 881-884 - 1994
- [j14]T. Hanif, Mark B. Sandler:
A counter-based Hough transform system. Microprocess. Microsystems 18(1): 19-26 (1994) - [c9]Jonathan P. Mackenzie, Mark B. Sandler:
Modelling Sound with Chaos. ISCAS 1994: 93-96 - [c8]M. Price, Mark B. Sandler:
Implementation of the IPFE Algorithm for Synthesis of High Order Recursive Filters. ISCAS 1994: 529-532 - 1993
- [j13]Luciano da Fontoura Costa, Mark B. Sandler:
Effective Detection of Digital Bar Segments with Hough Transform. CVGIP Graph. Model. Image Process. 55(3): 180-191 (1993) - [c7]Anthony R. Hare, Mark B. Sandler:
General test framework for straight-line detection by Hough transforms. ISCAS 1993: 239-242 - [c6]Mark B. Sandler:
Implementation of high order recursive filters as sub-filters. ISCAS 1993: 599-602 - [c5]Michael Waters, Mark B. Sandler:
Least squares IIR filter design on a logarithmic frequency scale. ISCAS 1993: 635-638 - 1992
- [j12]L. Hayat, A. A. Naqvi, Mark B. Sandler:
Comparative evaluation of fast thinning algorithms on a multiprocessor architecture. Image Vis. Comput. 10(4): 210-218 (1992) - [c4]C. K. Chan, Mark B. Sandler:
A complete shape recognition system using the Hough transform and neural network. ICPR (2) 1992: 21-24 - 1991
- [j11]S. Zhou, Mark B. Sandler, G. D. Bergman:
A switched memory decoding system for a multiple processor system. Microprocess. Microsystems 15(9): 481-487 (1991) - 1990
- [j10]D. Ben-Tzvi, A. A. Naqvi, Mark B. Sandler:
Synchronous multiprocessor implementation of the Hough transform. Comput. Vis. Graph. Image Process. 52(3): 437-446 (1990) - [j9]Mark B. Sandler, L. Hayat, Luciano da Fontoura Costa:
Benchmarking processors for image processing. Microprocess. Microsystems 14(9): 583-588 (1990) - [j8]D. Ben-Tzvi, Mark B. Sandler:
A combinatorial Hough transform. Pattern Recognit. Lett. 11(3): 167-174 (1990)
1980 – 1989
- 1989
- [j7]D. Ben-Tzvi, A. A. Naqvi, Mark B. Sandler:
Efficient parallel implementation of the Hough transform on a distributed memory system. Image Vis. Comput. 7(3): 167-172 (1989) - [j6]Doron Ben-Tzvi, Mark B. Sandler:
Efficient parallel implementation of the hough transform on a distributed memory system. Microprocessing and Microprogramming 27(1-5): 147-152 (1989) - [j5]Mark Sandler:
High complexity resonator structures for formant synthesis of musical instruments. Microprocessing and Microprogramming 27(1-5): 557-562 (1989) - [j4]Shirin Eghtesadi, Mark Sandler:
Implementation of the Hough transform for intermediate-level vision on a transputer network. Microprocess. Microsystems 13(3): 212-218 (1989) - [j3]Luciano da Fontoura Costa, Mark B. Sandler:
A binary Hough transform and its efficient implementation in a systolic array architecture. Pattern Recognit. Lett. 10(5): 329-334 (1989) - [c3]Violet F. Leavers, D. Ben-Tzvi, Mark B. Sandler:
A Dynamic Combinatorial Hough Transform for Straight Lines and Circles. Alvey Vision Conference 1989: 1-6 - [c2]Mark B. Sandler, L. Hayat, L. Costa, A. A. Naqvi:
A comparative evaluation of DSPs, microprocessors and the transputer for image processing. ICASSP 1989: 1532-1535 - 1988
- [j2]Mark B. Sandler, Shirin Eghtesadi:
Transputer based implementations of the hough transform for computer vision. Microprocess. Microprogramming 24(1-5): 403-408 (1988) - [j1]Mark B. Sandler:
Interfacing the transputer to the TMS320 in an image processing environment. Microprocess. Microsystems 12(9): 490-496 (1988) - [c1]Violet F. Leavers, Mark B. Sandler:
An Efficient Radon Transform. Pattern Recognition 1988: 380-389
Coauthor Index
[c155] [c151] [c149] [i26] [c145] [i25] [i23] [c134] [c132] [j47] [c127] [c126] [c118] [c111] [c110] [c109] [c108] [i16] [i15] [i13] [i12] [j45] [c105] [c99] [c98] [c96] [c95] [c94] [c93] [c92] [c91] [c89] [i10] [i9] [i7] [i6] [i5] [i4] [c88] [c87] [i1] [c82] [c81] [c77] [c76] [j41] [c75] [c74] [c73] [c72] [c71] [c69] [c68] [c67] [c66] [c65] [c64] [c63] [c62] [c59] [c58] [c57] [c52] [c48]
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