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2020 – today
- 2024
[j2]Yexu Zhou
, Haibin Zhao, Yiran Huang, Tobias Röddiger, Murat Kurnaz, Till Riedel, Michael Beigl:
AutoAugHAR: Automated Data Augmentation for Sensor-based Human Activity Recognition. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 8(2): 48:1-48:27 (2024)- [c14]Yiran Huang, Yexu Zhou, Haibin Zhao, Till Riedel, Michael Beigl:
A Survey on Wearable Human Activity Recognition: Innovative Pipeline Development for Enhanced Research and Practice. IJCNN 2024: 1-10 - [c13]Yexu Zhou, Haibin Zhao, Michael Hefenbrock, Siyan Li, Yiran Huang, Michael Beigl:
Deep Neural Network Pruning with Progressive Regularizer. IJCNN 2024: 1-10 - [c12]Yexu Zhou, Tobias King, Haibin Zhao, Yiran Huang, Till Riedel, Michael Beigl:
MLP-HAR: Boosting Performance and Efficiency of HAR Models on Edge Devices with Purely Fully Connected Layers. ISWC 2024: 133-139 - [c11]Yexu Zhou, Tobias King, Yiran Huang, Haibin Zhao, Till Riedel, Tobias Röddiger, Michael Beigl:
Enhancing Efficiency in HAR Models: NAS Meets Pruning. PerCom Workshops 2024: 33-38 - [c10]Yiran Huang, Yexu Zhou, Haibin Zhao, Till Riedel, Michael Beigl:
Optimizing AutoML for Tiny Edge Systems: A Baldwin-effect Inspired Genetic Algorithm. PerCom Workshops 2024: 160-165 - [c9]Yiran Huang, Yexu Zhou, Haibin Zhao, Likun Fang, Till Riedel, Michael Beigl:
ExTea: An Evolutionary Algorithm-Based Approach for Enhancing Explainability in Time-Series Models. ECML/PKDD (10) 2024: 429-446 - [i7]Yiran Huang, Haibin Zhao, Yexu Zhou, Till Riedel, Michael Beigl:
Standardizing Your Training Process for Human Activity Recognition Models: A Comprehensive Review in the Tunable Factors. CoRR abs/2401.05477 (2024) - [i6]Yiran Huang, Yexu Zhou, Haibin Zhao, Till Riedel, Michael Beigl:
Explainable Deep Learning Framework for Human Activity Recognition. CoRR abs/2408.11552 (2024) - 2023
- [c8]Yiran Huang, Nicole Schaal, Michael Hefenbrock, Yexu Zhou, Till Riedel, Michael Beigl:
McXai: Local Model-Agnostic Explanation As Two Games. IJCNN 2023: 1-8 - [i5]Yiran Huang, Yexu Zhou, Till Riedel, Likun Fang, Michael Beigl:
randomHAR: Improving Ensemble Deep Learners for Human Activity Recognition with Sensor Selection and Reinforcement Learning. CoRR abs/2307.07770 (2023) - [i4]Tobias King, Yexu Zhou, Tobias Röddiger, Michael Beigl:
MicroNAS: Memory and Latency Constrained Hardware-Aware Neural Architecture Search for Time Series Classification on Microcontrollers. CoRR abs/2310.18384 (2023) - 2022
- [j1]Nils Schwabe, Yexu Zhou, Leon Hielscher, Tobias Röddiger, Till Riedel, Sebastian Reiter:
Tools and methods for Edge-AI-systems. Autom. 70(9): 767-776 (2022) - [c7]Likun Fang, Ting Zhu, Erik Pescara, Yiran Huang, Yexu Zhou, Michael Beigl:
DragTapVib: An On-Skin Electromagnetic Drag, Tap, and Vibration Actuator for Wearable Computing. AHs 2022: 203-211 - [c6]Yiran Huang, Yexu Zhou, Michael Hefenbrock, Till Riedel, Likun Fang, Michael Beigl:
Universal Distributional Decision-Based Black-Box Adversarial Attack with Reinforcement Learning. ICONIP (3) 2022: 206-215 - [c5]Haibin Zhao, Yexu Zhou, Till Riedel, Michael Hefenbrock, Michael Beigl:
Improving Human Activity Recognition Models by Learnable Sparse Wavelet Layer. ISWC 2022: 84-88 - [c4]Yexu Zhou, Haibin Zhao, Yiran Huang, Till Riedel, Michael Hefenbrock, Michael Beigl:
TinyHAR: A Lightweight Deep Learning Model Designed for Human Activity Recognition. ISWC 2022: 89-93 - [c3]Yiran Huang, Yexu Zhou, Michael Hefenbrock, Till Riedel, Likun Fang, Michael Beigl:
Automatic Feature Engineering Through Monte Carlo Tree Search. ECML/PKDD (3) 2022: 581-598 - [i3]Yiran Huang, Nicole Schaal, Michael Hefenbrock, Yexu Zhou, Till Riedel, Likun Fang, Michael Beigl:
McXai: Local model-agnostic explanation as two games. CoRR abs/2201.01044 (2022) - [i2]Yiran Huang, Yexu Zhou, Michael Hefenbrock, Till Riedel, Likun Fang, Michael Beigl:
Universal Distributional Decision-based Black-box Adversarial Attack with Reinforcement Learning. CoRR abs/2211.08384 (2022) - 2020
- [c2]Yexu Zhou, Michael Hefenbrock, Yiran Huang, Till Riedel, Michael Beigl:
Automatic Remaining Useful Life Estimation Framework with Embedded Convolutional LSTM as the Backbone. ECML/PKDD (4) 2020: 461-477 - [i1]Yexu Zhou, Yuting Gao, Yiran Huang, Michael Hefenbrock, Till Riedel, Michael Beigl:
Automatic Remaining Useful Life Estimation Framework with Embedded Convolutional LSTM as the Backbone. CoRR abs/2008.03961 (2020)
2010 – 2019
- 2019
- [c1]Long Wang, Lennard Sommer, Till Riedel, Michael Beigl, Yexu Zhou, Yiran Huang:
NeuralIO: Indoor Outdoor Detection via Multimodal Sensor Data Fusion on Smartphones. SmartCity360° 2019: 127-138
Coauthor Index
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