| Sensing with earables: A systematic literature review and taxonomy of phenomena T Röddiger, C Clarke, P Breitling, T Schneegans, H Zhao, H Gellersen, ... Proceedings of the ACM on interactive, mobile, wearable and ubiquitous …, 2022 | 56 | 2022 |
| 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 | 31 | 2022 |
| Printed electrodermal activity sensor with optimized filter for stress detection H Zhao, A Scholz, M Beigl, S Ni, SA Singaraju, J Aghassi-Hagmann Proceedings of the 2022 ACM International Symposium on Wearable Computers …, 2022 | 8 | 2022 |
| Aging-aware training for printed neuromorphic circuits H Zhao, M Hefenbrock, M Beigl, MB Tahoori Proceedings of the 41st IEEE/ACM International Conference on Computer-Aided …, 2022 | 6 | 2022 |
| Highly-bespoke robust printed neuromorphic circuits H Zhao, B Sapui, M Hefenbrock, Z Yang, M Beigl, MB Tahoori 2023 Design, Automation & Test in Europe Conference & Exhibition (DATE), 1-6, 2023 | 5 | 2023 |
| Aircase: Earable charging case with air quality monitoring and soundscape sonification H Zhao, T Röddiger, M Beigl Adjunct Proceedings of the 2021 ACM International Joint Conference on …, 2021 | 5 | 2021 |
| 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 | 4 | 2024 |
| 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 | 3 | 2024 |
| Towards Temporal Information Processing–Printed Neuromorphic Circuits with Learnable Filters H Zhao, P Pal, M Hefenbrock, M Beigl, MB Tahoori Proceedings of the 18th ACM International Symposium on Nanoscale …, 2023 | 3 | 2023 |
| Power-aware training for energy-efficient printed neuromorphic circuits H Zhao, P Pal, M Hefenbrock, M Beigl, MB Tahoori 2023 IEEE/ACM International Conference on Computer Aided Design (ICCAD), 1-9, 2023 | 3 | 2023 |
| Improving Human Activity Recognition Models by Learnable Sparse Wavelet Layer H Zhao, Y Zhou, T Riedel, M Hefenbrock, M Beigl Proceedings of the 2022 ACM International Symposium on Wearable Computers, 84-88, 2022 | 3 | 2022 |
| 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 | 2 | 2024 |
| Analog Printed Spiking Neuromorphic Circuit P Pal, H Zhao, M Shatta, M Hefenbrock, SB Mamaghani, S Nassif, M Beigl, ... 2024 Design, Automation & Test in Europe Conference & Exhibition (DATE), 1-6, 2024 | 2 | 2024 |
| 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 | 2 | 2023 |
| Highly-dependable printed neuromorphic circuits based on additive manufacturing H Zhao, M Hefenbrock, M Beigl, MB Tahoori Flexible and Printed Electronics 8 (2), 025018, 2023 | 2 | 2023 |
| 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 | 1 | 2024 |
| Kalman Filtered Compressive Sensing Using Pseudo-Measurements H Zhao, C Funk, B Noack, U Hanebeck, M Beigl 2021 IEEE International Conference on Multisensor Fusion and Integration for …, 2021 | 1 | 2021 |
| 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 | | 2024 |
| Explainable Deep Learning Framework for Human Activity Recognition Y Huang, Y Zhou, H Zhao, T Riedel, M Beigl arXiv preprint arXiv:2408.11552, 2024 | | 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 | | 2024 |
Michael BeiglProfessor for Informatics, Karlsruhe Institute of Technology (KIT)在 teco.edu 的电子邮件经过验证
