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| Paper Abstract and Keywords | ||
| Presentation | 2020-03-08 17:40 Proposal of Data Augmentation Methods for Echo Sounder Image Analysis Min Jie, Soichiro Yokoyama, Tomohisa Yamashita, Hidenori Kawamura (Hokudai)  AI2019-54 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Data augmentation plays an important role in deep learning. Recently, RandAugment have been proposed as effective augmentation methods. In aquaculture, echo sounder image analysis is used for catching specific kind of fish to improve annual catches. Therefore, it remains significant to research for effects of different methods and find suitable augmentation method for echo sounder image analysis. This paper aims at finding effective settings for RandAugment by comparing effects of different transformation methods and figure out fitness of basic methods used in RandAugment for sonar image according to their variations with original images. The experiment results show improvement on recall rate and f1 score of distinguishing tuna in echo sounder images with suitable transformation methods. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Echo sounder image / Data Augmentation / RandAugment / Deep learning / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 469, AI2019-54, pp. 1-5, March 2020. | |
| Paper # | AI2019-54 | |
| Date of Issue | 2020-03-01 (AI) | |
| 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 | AI2019-54 |
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| Conference Information | |
| Committee | AI IPSJ-ICS JSAI-SAI JSAI-DOCMAS JSAI-KBS |
| Conference Date | 2020-03-08 - 2020-03-09 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Workshop of Social System and Information Technology (WSSIT20) |
| Paper Information | |
| Registration To | AI |
| Conference Code | 2020-03-AI-ICS-SAI-DOCMAS-KBS |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Proposal of Data Augmentation Methods for Echo Sounder Image Analysis |
| Sub Title (in English) | |
| Keyword(1) | Echo sounder image |
| Keyword(2) | Data Augmentation |
| Keyword(3) | RandAugment |
| Keyword(4) | Deep learning |
| Keyword(5) | |
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| Keyword(8) | |
| 1st Author's Name | Min Jie |
| 1st Author's Affiliation | Hokkaido University (Hokudai) |
| 2nd Author's Name | Soichiro Yokoyama |
| 2nd Author's Affiliation | Hokkaido University (Hokudai) |
| 3rd Author's Name | Tomohisa Yamashita |
| 3rd Author's Affiliation | Hokkaido University (Hokudai) |
| 4th Author's Name | Hidenori Kawamura |
| 4th Author's Affiliation | Hokkaido University (Hokudai) |
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| Speaker | Author-1 |
| Date Time | 2020-03-08 17:40:00 |
| Presentation Time | 20 minutes |
| Registration for | AI |
| Paper # | AI2019-54 |
| Volume (vol) | vol.119 |
| Number (no) | no.469 |
| Page | pp.1-5 |
| #Pages | 5 |
| Date of Issue | 2020-03-01 (AI) |
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