XAI-BayesHAR: A novel Framework for Human Activity Recognition with Integrated Uncertainty and Shapely Values
Author:
Affiliation:
1. Infineon Technologies,Munich,Germany
2. Infineon Technologies,Dublin,Ireland
3. Infineon Technologies,Irvine
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10068862/10068777/10069813.pdf?arnumber=10069813
Reference26 articles.
1. Deep Learning Models for Real-time Human Activity Recognition with Smartphones
2. Human Activity Classification Using mm-Wave FMCW Radar by Improved Representation Learning
3. One-Shot Learning for Robust Material Classification Using Millimeter-Wave Radar System
4. DeepFace: Closing the Gap to Human-Level Performance in Face Verification
5. Convolutional neural networks for human activity recognition using multiple accelerometer and gyroscope sensors
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1. Avian Activity Classification Using Recurrent Networks to Fuse Videos with Metadata on Imbalanced Datasets;Proceedings of the 2024 10th International Conference on Computing and Artificial Intelligence;2024-04-26
2. A Comprehensive Survey on Deep Learning Methods in Human Activity Recognition;Machine Learning and Knowledge Extraction;2024-04-18
3. Enhancing Human Activity Recognition: An Exploration of Machine Learning Models and Explainable AI Approaches for Feature Contribution Analysis;2023 International Conference on Energy, Materials and Communication Engineering (ICEMCE);2023-12-14
4. Toward Pioneering Sensors and Features Using Large Language Models in Human Activity Recognition;Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing;2023-10-08
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