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Hierarchical Signal Segmentation and Classification for Accurate Activity Recognition

  • Published:2018-10-08 Issue: Volume: Page:
  • ISSN:
  • Container-title:Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers
  • language:
  • Short-container-title:

Author:

Akbari Ali1,Wu Jian2,Grimsley Reese3,Jafari Roozbeh4

Affiliation:

1. Department of Biomedical Engineering, Texas A&M University

2. Department of Computer Science and Engineering, Texas A&M University

3. Department of Electrical and Computer Engineering, Texas A&M University

4. Department of Biomedical Engineering, Computer Science and Engineering, and Electrical and Computer Engineering, Texas A&M University

Funder

National Science Foundation

Publisher

ACM

Cited by 26 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Feature pyramid biLSTM: Using smartphone sensors for transportation mode detection;Transportation Research Interdisciplinary Perspectives;2024-07

2. Hierarchical Classifier for Improved Human Activity Recognition using Wearable Sensors;2024 IEEE International Instrumentation and Measurement Technology Conference (I2MTC);2024-05-20

3. Deep similarity segmentation model for sensor-based activity recognition;Multimedia Tools and Applications;2024-05-04

4. EEG Signals Decoding of Freely Moving Rats Based on Support Vector Machine Algorithm;2024 4th Asia Conference on Information Engineering (ACIE);2024-01-26

5. Adaptive Hierarchical Classification for Human Activity Recognition Using Inertial Measurement Unit (IMU) Time-Series Data;IEEE Access;2024
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