| Deep one-class classification L Ruff, R Vandermeulen, N Goernitz, L Deecke, SA Siddiqui, A Binder, ... International conference on machine learning, 4393-4402, 2018 | 706 | 2018 |
| DeepAnT: A deep learning approach for unsupervised anomaly detection in time series M Munir, SA Siddiqui, A Dengel, S Ahmed Ieee Access 7, 1991-2005, 2018 | 181 | 2018 |
| Automatic fish species classification in underwater videos: exploiting pre-trained deep neural network models to compensate for limited labelled data SA Siddiqui, A Salman, MI Malik, F Shafait, A Mian, MR Shortis, ... ICES Journal of Marine Science 75 (1), 374-389, 2018 | 132 | 2018 |
| Two-stage framework for optic disc localization and glaucoma classification in retinal fundus images using deep learning MN Bajwa, MI Malik, SA Siddiqui, A Dengel, F Shafait, W Neumeier, ... BMC medical informatics and decision making 19 (1), 1-16, 2019 | 61 | 2019 |
| Decnt: Deep deformable cnn for table detection SA Siddiqui, MI Malik, S Agne, A Dengel, S Ahmed IEEE Access 6, 74151-74161, 2018 | 58 | 2018 |
| Automatic fish detection in underwater videos by a deep neural network-based hybrid motion learning system A Salman, SA Siddiqui, F Shafait, A Mian, MR Shortis, K Khurshid, ... ICES Journal of Marine Science 77 (4), 1295-1307, 2020 | 55 | 2020 |
| FuseAD: Unsupervised anomaly detection in streaming sensors data by fusing statistical and deep learning models M Munir, SA Siddiqui, MA Chattha, A Dengel, S Ahmed Sensors 19 (11), 2451, 2019 | 50 | 2019 |
| Tsviz: Demystification of deep learning models for time-series analysis SA Siddiqui, D Mercier, M Munir, A Dengel, S Ahmed IEEE Access 7, 67027-67040, 2019 | 32 | 2019 |
| Computer-aided diagnosis of skin diseases using deep neural networks MN Bajwa, K Muta, MI Malik, SA Siddiqui, SA Braun, B Homey, A Dengel, ... Applied Sciences 10 (7), 2488, 2020 | 28 | 2020 |
| Deeptabstr: Deep learning based table structure recognition SA Siddiqui, IA Fateh, STR Rizvi, A Dengel, S Ahmed 2019 International Conference on Document Analysis and Recognition (ICDAR …, 2019 | 19 | 2019 |
| Rethinking semantic segmentation for table structure recognition in documents SA Siddiqui, PI Khan, A Dengel, S Ahmed 2019 International Conference on Document Analysis and Recognition (ICDAR …, 2019 | 18 | 2019 |
| Kinn: Incorporating expert knowledge in neural networks MA Chattha, SA Siddiqui, MI Malik, L van Elst, A Dengel, S Ahmed arXiv preprint arXiv:1902.05653, 2019 | 10 | 2019 |
| Tsxplain: Demystification of DNN decisions for time-series using natural language and statistical features M Munir, SA Siddiqui, F Küsters, D Mercier, A Dengel, S Ahmed International Conference on Artificial Neural Networks, 426-439, 2019 | 9 | 2019 |
| Handling editor: Howard Browman. Automatic Fish Species Classification in Underwater Videos: Exploiting Pre-Trained Deep Neural Network Models to Compensate for Limited … SA Siddiqui, A Salman, MI Malik, F Shafait, A Mian, MR Shortis, ... ICES J. Mar. Sci 75, 374-389, 2017 | 9 | 2017 |
| Fi-Fo Detector: Figure and Formula Detection Using Deformable Networks J Younas, SA Siddiqui, M Munir, MI Malik, F Shafait, P Lukowicz, S Ahmed Applied Sciences 10 (18), 6460, 2020 | 6 | 2020 |
| A wearable sensor based multi-criteria-decision-system for real-time seizure detection A Ahmed, W Ahmad, MJ Khan, SA Siddiqui, HM Cheema 2017 39th Annual International Conference of the IEEE Engineering in …, 2017 | 6 | 2017 |
| TSInsight: A Local-Global Attribution Framework for Interpretability in Time Series Data SA Siddiqui, D Mercier, A Dengel, S Ahmed Sensors 21 (21), 7373, 2021 | 5 | 2021 |
| Reliable model compression via label-preservation-aware loss functions V Joseph, SA Siddiqui, A Bhaskara, G Gopalakrishnan, S Muralidharan, ... arXiv preprint arXiv:2012.01604, 2020 | 4 | 2020 |
| Confident classification using a hybrid between deterministic and probabilistic convolutional neural networks MN Bajwa, S Khurram, M Munir, SA Siddiqui, MI Malik, A Dengel, ... IEEE Access 8, 115476-115485, 2020 | 4 | 2020 |
| DeepEX: Bridging the Gap Between Knowledge and Data Driven Techniques for Time Series Forecasting MA Chattha, SA Siddiqui, M Munir, MI Malik, L van Elst, A Dengel, ... International Conference on Artificial Neural Networks, 639-651, 2019 | 4 | 2019 |
Andreas DengelProfessor of Computer Science, University of Kaiserslautern & Executive Director, DFKIGeverifieerd e-mailadres voor dfki.de
