Paper Abstract and Keywords |
Presentation |
2020-12-11 13:40
Study of Deep Learning based Object Detection for Automatic Train Operation in Railways Shiva Krishna Maheshuni (UTokyo), Shimura Takahiro, Yabuki Kohei, Hasegawa Takumi (Kyosan Electric Mfg), Takeshi Mizuma (UTokyo) DC2020-61 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Real time object detection is already being implemented in systems like autonomous driving in cars, surveillance Cameras, factories, etc. But a very little application is being done in the field of railways. There are already various State of the Art object detectors which are trained on general open source image datasets like Open-Images 2019, MS-COCO , etc. The same object detectors cannot be used in the view point of railways. The aim of this paper is to refine and develop a YOLOv4 Object detector , which can aid in automatic train operation. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Object Detection / Convolutional neural networks(CNN) / Deep learning / YOLOv4 / Automatic Train Operation / / / |
Reference Info. |
IEICE Tech. Rep., vol. 120, no. 288, DC2020-61, pp. 12-17, Dec. 2020. |
Paper # |
DC2020-61 |
Date of Issue |
2020-12-04 (DC) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
Download PDF |
DC2020-61 |
Conference Information |
Committee |
DC |
Conference Date |
2020-12-11 - 2020-12-11 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
|
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
|
Paper Information |
Registration To |
DC |
Conference Code |
2020-12-DC |
Language |
English |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Study of Deep Learning based Object Detection for Automatic Train Operation in Railways |
Sub Title (in English) |
|
Keyword(1) |
Object Detection |
Keyword(2) |
Convolutional neural networks(CNN) |
Keyword(3) |
Deep learning |
Keyword(4) |
YOLOv4 |
Keyword(5) |
Automatic Train Operation |
Keyword(6) |
|
Keyword(7) |
|
Keyword(8) |
|
1st Author's Name |
Shiva Krishna Maheshuni |
1st Author's Affiliation |
University of Tokyo (UTokyo) |
2nd Author's Name |
Shimura Takahiro |
2nd Author's Affiliation |
Kyosan Electric Manufacturing Co., Ltd. (Kyosan Electric Mfg) |
3rd Author's Name |
Yabuki Kohei |
3rd Author's Affiliation |
Kyosan Electric Manufacturing Co., Ltd. (Kyosan Electric Mfg) |
4th Author's Name |
Hasegawa Takumi |
4th Author's Affiliation |
Kyosan Electric Manufacturing Co., Ltd. (Kyosan Electric Mfg) |
5th Author's Name |
Takeshi Mizuma |
5th Author's Affiliation |
University of Tokyo (UTokyo) |
6th Author's Name |
|
6th Author's Affiliation |
() |
7th Author's Name |
|
7th Author's Affiliation |
() |
8th Author's Name |
|
8th Author's Affiliation |
() |
9th Author's Name |
|
9th Author's Affiliation |
() |
10th Author's Name |
|
10th Author's Affiliation |
() |
11th Author's Name |
|
11th Author's Affiliation |
() |
12th Author's Name |
|
12th Author's Affiliation |
() |
13th Author's Name |
|
13th Author's Affiliation |
() |
14th Author's Name |
|
14th Author's Affiliation |
() |
15th Author's Name |
|
15th Author's Affiliation |
() |
16th Author's Name |
|
16th Author's Affiliation |
() |
17th Author's Name |
|
17th Author's Affiliation |
() |
18th Author's Name |
|
18th Author's Affiliation |
() |
19th Author's Name |
|
19th Author's Affiliation |
() |
20th Author's Name |
|
20th Author's Affiliation |
() |
Speaker |
Author-1 |
Date Time |
2020-12-11 13:40:00 |
Presentation Time |
20 minutes |
Registration for |
DC |
Paper # |
DC2020-61 |
Volume (vol) |
vol.120 |
Number (no) |
no.288 |
Page |
pp.12-17 |
#Pages |
6 |
Date of Issue |
2020-12-04 (DC) |
|