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| Presentation | 2016-08-08 14:30 Sugimoto Yudai, Sagara Kazutaka, Zhang Lifeng (Kyutech)  IE2016-49 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | This study is proposed on detection of Echizen Jellyfish from an image which was uploaded to the internet. The outbreak of Echizen Jellyfish will seriously damage the fishery of Japan. In this work, a machine learning algorithm such as SVM with the HOG feature was employed. All of the testee images were gathered from internet. There is no need to install underwater camera, and this method can reduce cost for detection. Also real observation requires so many people and times. On the other hands, proposed method requires only one person and can detect automatically. In this method, precision is lower than real observation, but this error can consider that slight effect on the consequence. The evaluation of this system is performed by using the F-measure. F-measure is a comprehensive evaluation of the precision and recall. In this study, system is created by manually. It means not completely automatic. This study aim to detect Echizen Jellyfish from internet by the automatically. From the above, this study is previous step for final aim. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | EtizenJellyfish / Outbreak / Machine Learning / Support Vector Machine / HOG-Feature / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 116, no. 176, IE2016-49, pp. 23-26, Aug. 2016. | |
| Paper # | IE2016-49 | |
| Date of Issue | 2016-08-01 (IE) | |
| ISSN | Print edition: ISSN 0913-5685 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 | IE2016-49 |
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| Conference Information | |
| Committee | IE ITE-ME IPSJ-AVM ITE-CE |
| Conference Date | 2016-08-08 - 2016-08-09 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | IE |
| Conference Code | 2016-08-IE-ME-AVM-CE |
| Language | Japanese without English title) |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | |
| Sub Title (in English) | |
| Keyword(1) | EtizenJellyfish |
| Keyword(2) | Outbreak |
| Keyword(3) | Machine Learning |
| Keyword(4) | Support Vector Machine |
| Keyword(5) | HOG-Feature |
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| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Sugimoto Yudai |
| 1st Author's Affiliation | Kyushu Institute of Technology (Kyutech) |
| 2nd Author's Name | Sagara Kazutaka |
| 2nd Author's Affiliation | Kyushu Institute of Technology (Kyutech) |
| 3rd Author's Name | Zhang Lifeng |
| 3rd Author's Affiliation | Kyushu Institute of Technology (Kyutech) |
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| Speaker | Author-1 |
| Date Time | 2016-08-08 14:30:00 |
| Presentation Time | 30 minutes |
| Registration for | IE |
| Paper # | IE2016-49 |
| Volume (vol) | vol.116 |
| Number (no) | no.176 |
| Page | pp.23-26 |
| #Pages | 4 |
| Date of Issue | 2016-08-01 (IE) |
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