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| Presentation | 2020-03-17 09:30 Object area extraction with biased training data set Ryo Nakamura, Yoshiaki Ueda, Jun Fujiki, Masaru Tanaka (Fukuoka Univ)  PRMU2019-88 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In order to extract an object region using machine learning, it is necessary to give a teacher label to each pixel. Providing a teacher label for each pixel is a very laborious task. In this paper, we propose a method to extract an area of an unidentified object without labeling every pixel by identifying the unidentified object with high precision. In this method, the training image set is not input as it is, but plural small patches are extracted from the training image set, and the discriminator is learned by using them as input. The learned discriminator extracts an object region by obtaining a discrimination ratio by using raster scan for an image to be extracted. At that time, though it is necessary to discriminate the non-discrimination object with high precision, by using the asymmetry of the training image set, the discrimination bias is utilized, and by discriminating the non-discrimination object with high precision, the region extraction of the discrimination object is carried out. And, visualization is carried out by making the identification ratio to be an image of αch. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | BTD / Object area extraction / / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 481, PRMU2019-88, pp. 115-119, March 2020. | |
| Paper # | PRMU2019-88 | |
| Date of Issue | 2020-03-09 (PRMU) | |
| 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 | PRMU2019-88 |
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| Conference Information | |
| Committee | PRMU IPSJ-CVIM |
| Conference Date | 2020-03-16 - 2020-03-17 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | PRMU |
| Conference Code | 2020-03-PRMU-CVIM |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Object area extraction with biased training data set |
| Sub Title (in English) | |
| Keyword(1) | BTD |
| Keyword(2) | Object area extraction |
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| 1st Author's Name | Ryo Nakamura |
| 1st Author's Affiliation | Fukuoka University (Fukuoka Univ) |
| 2nd Author's Name | Yoshiaki Ueda |
| 2nd Author's Affiliation | Fukuoka University (Fukuoka Univ) |
| 3rd Author's Name | Jun Fujiki |
| 3rd Author's Affiliation | Fukuoka University (Fukuoka Univ) |
| 4th Author's Name | Masaru Tanaka |
| 4th Author's Affiliation | Fukuoka University (Fukuoka Univ) |
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| Speaker | Author-1 |
| Date Time | 2020-03-17 09:30:00 |
| Presentation Time | 15 minutes |
| Registration for | PRMU |
| Paper # | PRMU2019-88 |
| Volume (vol) | vol.119 |
| Number (no) | no.481 |
| Page | pp.115-119 |
| #Pages | 5 |
| Date of Issue | 2020-03-09 (PRMU) |
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