| Deep one-class classification L Ruff, R Vandermeulen, N Goernitz, L Deecke, SA Siddiqui, A Binder, ... International conference on machine learning, 4393-4402, 2018 | 2238 | 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 | 597 | 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 | 262 | 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, 1-16, 2019 | 198 | 2019 |
| 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 | 171 | 2020 |
| Decnt: Deep deformable cnn for table detection SA Siddiqui, MI Malik, S Agne, A Dengel, S Ahmed IEEE access 6, 74151-74161, 2018 | 121 | 2018 |
| 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 | 102 | 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 | 102 | 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 | 93 | 2019 |
| 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 | 84 | 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 | 64 | 2019 |
| Metadata archaeology: Unearthing data subsets by leveraging training dynamics SA Siddiqui, N Rajkumar, T Maharaj, D Krueger, S Hooker arXiv preprint arXiv:2209.10015, 2022 | 23 | 2022 |
| 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 Artificial Neural Networks and Machine Learning–ICANN 2019: Workshop and …, 2019 | 23 | 2019 |
| Going beyond classification accuracy metrics in model compression V Joseph, SA Siddiqui, A Bhaskara, G Gopalakrishnan, S Muralidharan, ... arXiv preprint arXiv:2012.01604, 2020 | 19* | 2020 |
| 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 | 19 | 2020 |
| 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 | 14 | 2019 |
| 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 | 13 | 2021 |
| 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 | 13 | 2017 |
| Blockwise self-supervised learning at scale SA Siddiqui, D Krueger, Y LeCun, S Deny arXiv preprint arXiv:2302.01647, 2023 | 11 | 2023 |
| 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 | 10 | 2020 |
Andreas DengelProfessor of Computer Science, University of Kaiserslautern & Executive Director, DFKI在 dfki.de 的电子邮件经过验证
