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FuseAD: Unsupervised Anomaly Detection in Streaming Sensors Data by Fusing Statistical and Deep Learning Models.

, , , , and . Sensors, 19 (11): 2451 (2019)

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TSXplain: Demystification of DNN Decisions for Time-Series Using Natural Language and Statistical Features., , , , , and . ICANN (Workshop), volume 11731 of Lecture Notes in Computer Science, page 426-439. Springer, (2019)A Comparative Analysis of Traditional and Deep Learning-Based Anomaly Detection Methods for Streaming Data., , , and . ICMLA, page 561-566. IEEE, (2019)Pattern-Based Contextual Anomaly Detection in HVAC Systems., , , and . ICDM Workshops, page 1066-1073. IEEE Computer Society, (2017)Knowledge-Aware Object Detection in Traffic Scenes., , , , and . ICAART (3), page 617-624. SCITEPRESS, (2024)DeepCeNS: An end-to-end Pipeline for Cell and Nucleus Segmentation in Microscopic Images., , , , , , , and . IJCNN, page 1-8. IEEE, (2021)F2DNet: Fast Focal Detection Network for Pedestrian Detection., , , and . ICPR, page 4658-4664. IEEE, (2022)A Hybrid Framework for Time-series Analysis: From Anomaly Detection to Uncertainty Estimation and Explainability.. Kaiserslautern University of Technology, Germany, (2021)Point2Mask: A Weakly Supervised Approach for Cell Segmentation Using Point Annotation., , , , , , , , , and . MIUA, volume 13413 of Lecture Notes in Computer Science, page 139-153. Springer, (2022)DeepEX: Bridging the Gap Between Knowledge and Data Driven Techniques for Time Series Forecasting., , , , , , and . ICANN (2), volume 11728 of Lecture Notes in Computer Science, page 639-651. Springer, (2019)XAI Handbook: Towards a Unified Framework for Explainable AI., , , , , and . ICCVW, page 3759-3768. IEEE, (2021)