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, 2019 | 218 | 2019 |
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), 2019 | 55 | 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 | 40 | 2019 |
Pattern-Based Contextual Anomaly Detection in HVAC Systems M Munir, S Erkel, A Dengel, S Ahmed 2017 IEEE International Conference on Data Mining Workshops (ICDMW), 1066-1073, 2017 | 16 | 2017 |
A Comparative Analysis of Traditional and Deep Learning-based Anomaly Detection Methods for Streaming Data M Munir, MA Chattha, A Dengel, S Ahmed 18th IEEE International Conference on Machine Learning and Applications (ICMLA), 2019 | 15 | 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 (ICANN) 11731, 426–439, 2019 | 12 | 2019 |
Data Analytics: Industrial Perspective & Solutions for Streaming Data M Munir, S Baumbach, Y Gu, A Dengel, S Ahmed by Last M., Kandel A., Bunke H., Series in Machine Perception and Artificial …, 2018 | 8 | 2018 |
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 |
XAI Handbook: Towards a Unified Framework for Explainable AI S Palacio, A Lucieri, M Munir, S Ahmed, J Hees, A Dengel Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 5 | 2021 |
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 | 3 | 2019 |
Evaluating Privacy-Preserving Machine Learning in Critical Infrastructures: A Case Study on Time-Series Classification D Mercier, A Lucieri, M Munir, A Dengel, A Sheraz IEEE Transactions on Industrial Informatics, 2021 | 1 | 2021 |
DeepCIS: An end-to-end Pipeline for Cell-type aware Instance Segmentation in Microscopic Images N Khalid, M Munir, C Edlund, TR Jackson, J Trygg, R Sjögren, A Dengel, ... 2021 IEEE EMBS International Conference on Biomedical and Health Informatics …, 2021 | 1 | 2021 |
DeepCeNS: An end-to-end Pipeline for Cell and Nucleus Segmentation in Microscopic Images N Khalid, M Munir, C Edlund, TR Jackson, J Trygg, R Sjögren, A Dengel, ... 2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021 | 1 | 2021 |
Knowledge Augmented Machine Learning with Applications in Autonomous Driving: A Survey J Wörmann, D Bogdoll, E Bührle, H Chen, EF Chuo, K Cvejoski, L van Elst, ... arXiv preprint arXiv:2205.04712, 2022 | | 2022 |
PPML-TSA: A modular privacy-preserving time series classification framework D Mercier, A Lucieri, M Munir, A Dengel, S Ahmed Software Impacts, 100286, 2022 | | 2022 |
F2DNet: Fast Focal Detection Network for Pedestrian Detection AH Khan, M Munir, L van Elst, A Dengel arXiv preprint arXiv:2203.02331, 2022 | | 2022 |
DeepMuCS: A Framework for Mono-& Co-culture Microscopic Image Analysis: From Generation to Segmentation N Khalid, M Koochali, V Rajashekhar, M Munir, C Edlund, T Jackson, ... TechRxiv, 2022 | | 2022 |
A Hybrid Framework for Time-series Analysis - From Anomaly Detection to Uncertainty Estimation and Explainability M Munir https://doi.org/10.26204/KLUEDO/6703, 2021 | | 2021 |