Fast Pedestrian Detection in Surveillance Video Based on Soft Target Training of Shallow Random Forest

Fast Pedestrian Detection in Surveillance Video Based on Soft Target Training of Shallow Random Forest

In recent years, deep learning algorithms have achieved top performances in object detection tasks. However, in real-time, systems having memory or computing limitations very wide and deep networks with numerous parameters constitute a major obstacle. In this paper, we propose a fast method for dete...

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Bibliographic Details
Main Authors: Sangjun Kim, Sooyeong Kwak, Byoung Chul Ko
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Pedestrian detection
model compression
teacher-student framework
random forest
shallower RF
surveillance video
Online Access:https://ieeexplore.ieee.org/document/8610075/

Internet

https://ieeexplore.ieee.org/document/8610075/

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