Enhanced Video Classification System with Convolutional Neural Networks Using Representative Frames as Input Data

Author:

Jayasree K.,Idicula Sumam Mary

Publisher

Springer Nature Singapore

Reference9 articles.

1. Ferman, A. M., & Tekalp, A. M. (1999). Probabilistic analysis and extraction of videocontent. In Proceedings of ICIP (vol. 2, pp 91–95).

2. Yuan, Y., Song, Q. -B., & Shen, J. -Y. (2002) Automatic video classification using decision tree method. In Proceedings of Machine Learning and Cybernetics (pp. 1153–1157).

3. Karpathy, A., Toderici, G., Shetty, S., Leung, T., Sukthankar, R., & Fei-Fei, L. (2014). Large-scale video classification with convolutional neural networks. In Proceedings of International Computer Vision and Pattern Recognition (CVPR 2014) . IEEE.

4. Simonyan, K., & Zisserman, A. (2014). Two stream convolutional networks for action recognition in videos. CoRR abs/1406.2199:1-8

5. Bhardwaj, Shweta, Mukundhan Srinivasan, and Mitesh M. Khapra. ”Efficient videoclassification using fewer frames.” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2019.

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