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| Presentation | 2018-12-14 14:40 Calving sign detection with cattle state-based feature extraction from video frames Ryosuke Hyodo, Saki Yasuda (Waseda Univ.), Susumu Saito (Waseda Univ./iflab, inc.), Yusuke Okimoto (Waseda Univ.), Teppei Nakano, Makoto Akabane (Waseda Univ./iflab, inc.), Tetsunori Kobayashi, Tetsuji Ogawa (Waseda Univ.)  PRMU2018-90 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Requirements that camera-based automatic calving sign detection should meet are established and a system satisfying these requirements is successfully designed. Upon deployment of such camera-based detection, the system needs to be 1) working with small data (because calving does not happen frequently), 2) robust to changing environments, and 3) explainable for reasons of the prediction results. However, there requirements are not realistic for end-to-end approaches (i.e., prediction with a single DNN). This study presents a two-stage calving prediction system, in which calving-relevant information obtained by DNN-based feature extractor is taken as inputs to another DNN-based calving sign detector. Experimental comparisons demonstrated that the developed system achieved a calving precision ratio of 80% and a calving recall ratio of 88%. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | neural network / calving prediction / image recognition / precision livestock farming / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 118, no. 362, PRMU2018-90, pp. 79-84, Dec. 2018. | |
| Paper # | PRMU2018-90 | |
| Date of Issue | 2018-12-06 (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 | PRMU2018-90 |
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| Conference Information | |
| Committee | PRMU |
| Conference Date | 2018-12-13 - 2018-12-14 |
| 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 | 2018-12-PRMU |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Calving sign detection with cattle state-based feature extraction from video frames |
| Sub Title (in English) | |
| Keyword(1) | neural network |
| Keyword(2) | calving prediction |
| Keyword(3) | image recognition |
| Keyword(4) | precision livestock farming |
| Keyword(5) | |
| Keyword(6) | |
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| Keyword(8) | |
| 1st Author's Name | Ryosuke Hyodo |
| 1st Author's Affiliation | Waseda University (Waseda Univ.) |
| 2nd Author's Name | Saki Yasuda |
| 2nd Author's Affiliation | Waseda University (Waseda Univ.) |
| 3rd Author's Name | Susumu Saito |
| 3rd Author's Affiliation | Waseda University/inteligent framework, inc. (Waseda Univ./iflab, inc.) |
| 4th Author's Name | Yusuke Okimoto |
| 4th Author's Affiliation | Waseda University (Waseda Univ.) |
| 5th Author's Name | Teppei Nakano |
| 5th Author's Affiliation | Waseda University/inteligent framework, inc. (Waseda Univ./iflab, inc.) |
| 6th Author's Name | Makoto Akabane |
| 6th Author's Affiliation | Waseda University/inteligent framework, inc. (Waseda Univ./iflab, inc.) |
| 7th Author's Name | Tetsunori Kobayashi |
| 7th Author's Affiliation | Waseda University (Waseda Univ.) |
| 8th Author's Name | Tetsuji Ogawa |
| 8th Author's Affiliation | Waseda University (Waseda Univ.) |
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| Speaker | Author-1 |
| Date Time | 2018-12-14 14:40:00 |
| Presentation Time | 15 minutes |
| Registration for | PRMU |
| Paper # | PRMU2018-90 |
| Volume (vol) | vol.118 |
| Number (no) | no.362 |
| Page | pp.79-84 |
| #Pages | 6 |
| Date of Issue | 2018-12-06 (PRMU) |
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