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Pedestrian Detection Based on Deep L...

Chen, Li.

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Pedestrian Detection Based on Deep Learning.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Pedestrian Detection Based on Deep Learning./
Author:	Chen, Li.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2017,
Description:	55 p.
Notes:	Source: Masters Abstracts International, Volume: 57-04.
Contained By:	Masters Abstracts International57-04(E).
Subject:	Electrical engineering. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10622123
ISBN:	9780355472189

Pedestrian Detection Based on Deep Learning.
Chen, Li.

Pedestrian Detection Based on Deep Learning. - Ann Arbor : ProQuest Dissertations & Theses, 2017 - 55 p.

Source: Masters Abstracts International, Volume: 57-04.

Thesis (M.S.)--University of California, Riverside, 2017.

In general, researchers use hand-crafted methods or combine with the deep learning to solve the problem of Pedestrian Detection. In this paper, this problem can be implemented in the purely convolution neural network. Region Proposal Network, proposed by the algorithm for objects detection could be modified and applied on the pedestrian detection. After getting feature maps from the pretrained model, feed them into the new model and train by using Tensorflow as the deep learning framework, we can get the predicted bounding boxes that contain the pedestrians. This method is efficient and can reach the accuracy around 80 percent.

ISBN: 9780355472189Subjects--Topical Terms:

649834
Electrical engineering.

Pedestrian Detection Based on Deep Learning.
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245 1 0 $a Pedestrian Detection Based on Deep Learning.
260 1 $a Ann Arbor : $b ProQuest Dissertations & Theses, $c 2017
300 $a 55 p.
500 $a Source: Masters Abstracts International, Volume: 57-04.
500 $a Adviser: Qi Zhu.
502 $a Thesis (M.S.)--University of California, Riverside, 2017.
520 $a In general, researchers use hand-crafted methods or combine with the deep learning to solve the problem of Pedestrian Detection. In this paper, this problem can be implemented in the purely convolution neural network. Region Proposal Network, proposed by the algorithm for objects detection could be modified and applied on the pedestrian detection. After getting feature maps from the pretrained model, feed them into the new model and train by using Tensorflow as the deep learning framework, we can get the predicted bounding boxes that contain the pedestrians. This method is efficient and can reach the accuracy around 80 percent.
590 $a School code: 0032.
650 4 $a Electrical engineering. $3 649834
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710 2 $a University of California, Riverside. $b Electrical Engineering. $3 1669528
773 0 $t Masters Abstracts International $g 57-04(E).
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791 $a M.S.
792 $a 2017
793 $a English
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=10622123