| Tinyhar: A lightweight deep learning model designed for human activity recognition Y Zhou, H Zhao, Y Huang, T Riedel, M Hefenbrock, M Beigl Proceedings of the 2022 ACM International Symposium on Wearable Computers, 89-93, 2022 | 43 | 2022 |
| Automatic remaining useful life estimation framework with embedded convolutional LSTM as the backbone Y Zhou, M Hefenbrock, Y Huang, T Riedel, M Beigl Machine Learning and Knowledge Discovery in Databases: Applied Data Science …, 2021 | 21 | 2021 |
| NeuralIO: Indoor outdoor detection via multimodal sensor data fusion on smartphones L Wang, L Sommer, T Riedel, M Beigl, Y Zhou, Y Huang Science and Technologies for Smart Cities: 5th EAI International Summit …, 2020 | 13 | 2020 |
| Automatic feature engineering through Monte Carlo tree search Y Huang, Y Zhou, M Hefenbrock, T Riedel, L Fang, M Beigl Joint European Conference on Machine Learning and Knowledge Discovery in …, 2022 | 10 | 2022 |
| DragTapVib: An on-skin electromagnetic drag, tap, and vibration actuator for wearable computing L Fang, T Zhu, E Pescara, Y Huang, Y Zhou, M Beigl Proceedings of the Augmented Humans International Conference 2022, 203-211, 2022 | 10 | 2022 |
| Investigating Passive Haptic Learning of Piano Songs Using Three Tactile Sensations of Vibration, Stroking and Tapping L Fang, T Müller, E Pescara, N Fischer, Y Huang, M Beigl Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2023 | 9 | 2023 |
| McXai: local model-agnostic explanation as two games Y Huang, N Schaal, M Hefenbrock, Y Zhou, T Riedel, M Beigl 2023 International Joint Conference on Neural Networks (IJCNN), 01-08, 2023 | 8 | 2023 |
| A survey on wearable human activity recognition: innovative pipeline development for enhanced research and practice Y Huang, Y Zhou, H Zhao, T Riedel, M Beigl 2024 International Joint Conference on Neural Networks (IJCNN), 1-10, 2024 | 6 | 2024 |
| AutoAugHAR: Automated Data Augmentation for Sensor-based Human Activity Recognition Y Zhou, H Zhao, Y Huang, T Röddiger, M Kurnaz, T Riedel, M Beigl Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous …, 2024 | 6 | 2024 |
| Enhancing Efficiency in HAR Models: NAS Meets Pruning Y Zhou, T King, Y Huang, H Zhao, T Riedel, T Röddiger, M Beigl 2024 IEEE International Conference on Pervasive Computing and Communications …, 2024 | 6 | 2024 |
| Universal distributional decision-based black-box adversarial attack with reinforcement learning Y Huang, Y Zhou, M Hefenbrock, T Riedel, L Fang, M Beigl International Conference on Neural Information Processing, 206-215, 2022 | 6 | 2022 |
| State Graph Based Explanation Approach for Black-Box Time Series Model Y Huang, C Li, H Lu, T Riedel, M Beigl World Conference on Explainable Artificial Intelligence, 153-164, 2023 | 4 | 2023 |
| Standardizing Your Training Process for Human Activity Recognition Models–A Comprehensive Review in the Tunable Factors Y Huang, H Zhao, Y Zhou, T Riedel, M Beigl International Conference on Mobile and Ubiquitous Systems: Computing …, 2023 | 3 | 2023 |
| randomHAR: Improving Ensemble Deep Learners for Human Activity Recognition with Sensor Selection and Reinforcement Learning Y Huang, Y Zhou, T Riedel, L Fang, M Beigl arXiv preprint arXiv:2307.07770, 2023 | 3 | 2023 |
| HOW DOES THE BITCOIN SENTIMENT INDEX OF FEAR & GREED AFFECT BITCOIN RETURNS? Y Huang, T Xu, C Xue, J Zhang | 3 | 2022 |
| MLP-HAR: Boosting Performance and Efficiency of HAR Models on Edge Devices with Purely Fully Connected Layers Y Zhou, T King, H Zhao, Y Huang, T Riedel, M Beigl Proceedings of the 2024 ACM International Symposium on Wearable Computers …, 2024 | 2 | 2024 |
| Optimizing AutoML for Tiny Edge Systems: A Baldwin-effect Inspired Genetic Algorithm Y Huang, Y Zhou, H Zhao, T Riedel, M Beigl 2024 IEEE International Conference on Pervasive Computing and Communications …, 2024 | 2 | 2024 |
| Generate Explanations for Time-series classification by ChatGPT Z Xue, Y Huang, H Ma, M Beigl Explainable Artificial Intelligence. Springer, 2024 | 2 | 2024 |
| ExTea: An Evolutionary Algorithm-Based Approach for Enhancing Explainability in Time-Series Models Y Huang, Y Zhou, H Zhao, L Fang, T Riedel, M Beigl Joint European Conference on Machine Learning and Knowledge Discovery in …, 2024 | 1 | 2024 |
| Deep Neural Network Pruning with Progressive Regularizer Y Zhou, H Zhao, M Hefenbrock, S Li, Y Huang, M Beigl 2024 International Joint Conference on Neural Networks (IJCNN), 1-10, 2024 | 1 | 2024 |
Michael BeiglProfessor for Informatics, Karlsruhe Institute of Technology (KIT)Verified email at teco.edu