Light-field imaging for distinguishing fake pedestrians using convolutional neural networks
Pedestrian detection plays an important role in automatic driving system and intelligent robots, and has made great progress in recent years. Identifying the pedestrians from confused planar objects is a challenging problem in the field of pedestrian recognition. In this article, we focus on the 2D...
Main Authors: | Yufeng Zhao, Meng Zhao, Fan Shi, Chen Jia, Shengyong Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
SAGE Publishing
2021-02-01
|
Series: | International Journal of Advanced Robotic Systems |
Online Access: | https://doi.org/10.1177/1729881420987400 |
Similar Items
-
Identification of Pedestrians From Confused Planar Objects Using Light Field Imaging
by: Chen Jia, et al.
Published: (2018-01-01) -
Detecting Small Scale Pedestrians and Anthropomorphic Negative Samples Based on Light-Field Imaging
by: Yufeng Zhao, et al.
Published: (2020-01-01) -
OPCNN-FAKE: Optimized Convolutional Neural Network for Fake News Detection
by: Hager Saleh, et al.
Published: (2021-01-01) -
An Intelligent Pedestrian Image Tracking System Based on Convolutional Neural Network
by: Lin, Yu-Hao, et al.
Published: (2018) -
Pedestrian trajectory prediction with Convolutional Neural Networks
by: Zamboni, Simone
Published: (2020)