A convolutional neural‐network‐based pedestrian counting model for various crowded scenes

Author:

Shen Jie1,Xiong Xin1,Xue Zhiyuan1,Bian Yinglong1

Affiliation:

1. School of Computer Science & EngineeringUniversity of Electronic Science and Technology of China Chengdu China

Funder

National Science and Technology Major Project Foundation of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Graphics and Computer-Aided Design,Computer Science Applications,Civil and Structural Engineering

Reference99 articles.

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2. Agostinelli F. Anderson M. R. &Lee H.(2013).Adaptive multi‐column deep neural networks with application to robust image denoising. InProceedings of Advances in Neural Information Processing Systems(pp. 1493–1501) Lake Tahoe Nevada.

3. Almeida J. E. Rosseti R. J. &Coelho A. L.(2013).Crowd simulation modeling applied to emergency and evacuation simulations using multi‐agent systems. InDSIE'11 ‐ 6th Doctoral Symposium on Informatics Engineering Engineering(pp. 93–104) Faculty of Porto University Porto.

4. An adaptive people counting system with dynamic features selection and occlusion handling

5. Bala Subburaman V. Descamps A. &Carincotte C.(2012).Counting people in the crowd using a generic head detector. InProceedings of IEEE International Workshop on Performance Evaluation of Tracking and Surveillance(pp. 470–475) IEEE Beijing China.

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