| Automatic speech recognition and speech variability: A review M Benzeghiba, R De Mori, O Deroo, S Dupont, T Erbes, D Jouvet, ... Speech communication 49 (10-11), 763-786, 2007 | 744 | 2007 |
| Signal analysis: wavelets, filter banks, time-frequency transforms and applications A Mertins, DA Mertins John Wiley & Sons, Inc., 1999 | 670 | 1999 |
| Compressed sensing reconstruction for magnetic resonance parameter mapping M Doneva, P Börnert, H Eggers, C Stehning, J Sénégas, A Mertins Magnetic resonance in medicine 64 (4), 1114-1120, 2010 | 468 | 2010 |
| Sketch-based image matching using angular partitioning A Chalechale, G Naghdy, A Mertins IEEE Transactions on Systems, Man, and Cybernetics-part a: systems and …, 2004 | 217 | 2004 |
| XSleepNet: Multi-view sequential model for automatic sleep staging H Phan, OY Chén, MC Tran, P Koch, A Mertins, M De Vos IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (9), 5903-5915, 2021 | 196 | 2021 |
| Sleeptransformer: Automatic sleep staging with interpretability and uncertainty quantification H Phan, K Mikkelsen, OY Chén, P Koch, A Mertins, M De Vos IEEE Transactions on Biomedical Engineering 69 (8), 2456-2467, 2022 | 171 | 2022 |
| Random regression forests for acoustic event detection and classification H Phan, M Maaß, R Mazur, A Mertins IEEE/ACM Transactions on Audio, Speech, and Language Processing 23 (1), 20-31, 2014 | 154 | 2014 |
| Improving GANs for speech enhancement H Phan, IV McLoughlin, L Pham, OY Chén, P Koch, M De Vos, A Mertins IEEE Signal Processing Letters 27, 1700-1704, 2020 | 149 | 2020 |
| Robust audio event recognition with 1-max pooling convolutional neural networks H Phan, L Hertel, M Maass, A Mertins arXiv preprint arXiv:1604.06338, 2016 | 142 | 2016 |
| Signaltheorie A Mertins Teubner, 1996 | 135 | 1996 |
| Towards more accurate automatic sleep staging via deep transfer learning H Phan, OY Chén, P Koch, Z Lu, I McLoughlin, A Mertins, M De Vos IEEE Transactions on Biomedical Engineering 68 (6), 1787-1798, 2020 | 130 | 2020 |
| Edge image description using angular radial partitioning A Chalechale, A Mertins, G Naghdy IEE Proceedings-Vision, Image and Signal Processing 151 (2), 93-101, 2004 | 119 | 2004 |
| Oldenburg logatome speech corpus (OLLO) for speech recognition experiments with humans and machines. T Wesker, BT Meyer, K Wagener, J Anemüller, A Mertins, B Kollmeier Interspeech, 1273-1276, 2005 | 110 | 2005 |
| Compressed sensing for chemical shift‐based water–fat separation M Doneva, P Börnert, H Eggers, A Mertins, J Pauly, M Lustig Magnetic resonance in medicine 64 (6), 1749-1759, 2010 | 106 | 2010 |
| Room Impulse Response Shortening/Reshaping With Infinity- and -Norm Optimization A Mertins, T Mei, M Kallinger IEEE Transactions on Audio, Speech, and Language Processing 18 (2), 249-259, 2009 | 105 | 2009 |
| CNN-MoE based framework for classification of respiratory anomalies and lung disease detection L Pham, H Phan, R Palaniappan, A Mertins, I McLoughlin IEEE journal of biomedical and health informatics 25 (8), 2938-2947, 2021 | 91 | 2021 |
| Local region descriptors for active contours evolution C Darolti, A Mertins, C Bodensteiner, UG Hofmann IEEE Transactions on Image Processing 17 (12), 2275-2288, 2008 | 91 | 2008 |
| Improved audio scene classification based on label-tree embeddings and convolutional neural networks H Phan, L Hertel, M Maass, P Koch, R Mazur, A Mertins IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (6), 1278 …, 2017 | 84 | 2017 |
| Audio scene classification with deep recurrent neural networks H Phan, P Koch, F Katzberg, M Maass, R Mazur, A Mertins arXiv preprint arXiv:1703.04770, 2017 | 82 | 2017 |
| Comparing time and frequency domain for audio event recognition using deep learning L Hertel, H Phan, A Mertins 2016 international joint conference on neural networks (IJCNN), 3407-3411, 2016 | 82 | 2016 |
