Reconfigurable Pedestrian Detection System Using Deep Learning for Video Surveillance
Author:
Affiliation:
1. Anna University
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Subject
Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software
Link
https://www.jstage.jst.go.jp/article/transinf/E106.D/9/E106.D_2019EDL8132/_pdf
Reference23 articles.
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2. [2] V. Murugan, V.R. Vijaykumar, and A. Nidhila, “A Deep learning RCNN approach for vehicle recognition in traffic surveillance system,” Int. Conf. Comm. Sig. Proc., 2019. 10.1109/iccsp.2019.8698018
3. [3] A. Ullah, H. Xie, M.O. Farooq, and Z. Sun, “Pedestrian detection in infrared images using fast RCNN,” IPTA, vol.8, 2018. 10.1109/ipta.2018.8608121
4. [4] M.-C. Roh and J.-Y. Lee, “Refining faster-RCNN for accurate object detection,” IAPR Int. Conf. MVA, vol.15, pp.514-517, 2017. 10.23919/mva.2017.7986913
5. [5] V. Pham, P. Vo, V.T. Hung, and L.H. Bac, “GPU implementation of extended Gaussian mixture model for background subtraction,” IEEE International Conference on Computing and Communication Technologies, Research, Innovation, and Vision for the Future, pp.1-4, Nov. 2010. 10.1109/rivf.2010.5634007
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