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Pedestrian Detection and Location Algorithm Based on Deep Learning

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成果类型:
会议论文
作者:
Xie Chuang*;Li Pin;Sun Yurong
通讯作者:
Xie Chuang
作者机构:
[Sun Yurong; Xie Chuang; Li Pin] Cent South Univ Forestry & Technol, Dept Sci, Changsha 410000, Hunan, Peoples R China.
通讯机构:
[Xie Chuang] C
Cent South Univ Forestry & Technol, Dept Sci, Changsha 410000, Hunan, Peoples R China.
语种:
英文
关键词:
pedestrian detection;CNN;deep learning;YOLO
期刊:
2019 INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION, BIG DATA & SMART CITY (ICITBS)
年:
2019
页码:
582-585
会议名称:
International Conference on Intelligent Transportation, Big Data & Smart City (ICITBS)
会议时间:
JAN 12-13, 2019
会议地点:
Changsha, PEOPLES R CHINA
会议主办单位:
[Xie Chuang;Li Pin;Sun Yurong] Cent South Univ Forestry & Technol, Dept Sci, Changsha 410000, Hunan, Peoples R China.
出版地:
345 E 47TH ST, NEW YORK, NY 10017 USA
出版者:
IEEE
ISBN:
978-1-7281-1307-4
机构署名:
本校为第一且通讯机构
摘要:
This paper studies the insufficient extracted image feature in CNN basic network towards large model parameters quantity in convolutional neural network-based target detection model. First, it analyzes calculating method and parameter quantity of separable convolution and standard convolution, and processes original image through increasing sampling layer and blocking area extraction layer on Kronecker. Then, original image will be sampled with two different ratios to form image pyramid sequence and splice two-layered pyramid image in order to guarantee the same original image size. Furthermor...

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