Human Activity Recognition based on Deep Belief Network Classifier and Combination of Local and Global Features

Author:

Mahmoodzadeh Azar

Publisher

CMV Verlag

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Computer Vision and Pattern Recognition,Information Systems

Reference38 articles.

1. [1] S. Ranasinghe, F. Al Machot, and H.C. Mayr, "A review on applications of activity recognition systems with regard to performance and evaluation," International Journal of Distributed Sensor Networks, vol. 12, no. 8, p. 1550147716665520, 2016.

2. [2] S.S. Agaian, J. Tang, and J. Tan, "Electronic imaging applications in mobile healthcare," 2019.

3. [3] Y. Wang, H. Jiang, M.S. Drew, Z.N. Li, and G. Mori, "Unsupervised discovery of action classes," in Proceedings of CVPR, pp. 17-22.

4. [4] S. Yan, J.S. Smith, W. Lu, and B. Zhang, "Multibranch Attention Networks for Action Recognition in Still Images," IEEE Transactions on Cognitive and Developmental Systems, vol. 10, no. 4, pp. 1116-1125, 2017.

5. [5] Y. Wang, Y. Li, X. Ji, "Human action recognition based on global gist feature and local patch coding," International Journal of Signal Processing, Image Processing and Pattern Recognition, vol. 8, no. 2, pp. 235-246, 2015.

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