Lightweight convolutional neural network-based pedestrian detection and re-identification in multiple scenarios

Xiao Ke; Xinru Lin; Liyun Qin

doi:10.1007/s00138-021-01169-7

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Lightweight convolutional neural network-based pedestrian detection and re-identification in multiple scenarios

Xiao Ke Xinru Lin Liyun Qin

Year: 2021 Journal: Machine Vision and Applications Vol: 32 (2) Publisher: Springer Science+Business Media

DOI: 10.1007/s00138-021-01169-7

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Keywords:

Pedestrian Pedestrian detection Computer science Artificial intelligence Computer vision Convolutional neural network Object detection Identification (biology) Pattern recognition (psychology) Engineering Transport engineering

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Topics

Video Surveillance and Tracking Methods

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Advanced Neural Network Applications

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Autonomous Vehicle Technology and Safety

Physical Sciences → Engineering → Automotive Engineering

Lightweight convolutional neural network-based pedestrian detection and re-identification in multiple scenarios

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Citation History

Topics

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