Current Result Document :
| 한글제목(Korean Title) |
돼지 공격 행동 모니터링을 위한 영상 기반의 경량화 시스템 |
| 영문제목(English Title) |
Lightweight Video-based Approach for Monitoring Pigs’ Aggressive Behavior |
| 저자(Author) |
하싼
이종욱
오스만
박대희
정용화
Hassan Seif Mluba
Jonguk Lee
Othmane Atif
Daihee Park
Yongwha Chung
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| 원문수록처(Citation) |
VOL 28 NO. 02 PP. 0704 ~ 0707 (2021. 11) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Pigs’ aggressive behavior represents one of the common issues that occur inside pigpens and which harm pigs’ health and welfare, resulting in a financial burden to farmers. Continuously monitoring several pigs for 24 hours to identify those behaviors manually is a very difficult task for pig caretakers. In this study, we propose a lightweight video-based approach for monitoring pigs’ aggressive behavior that can be implemented even in small-scale farms. The proposed system receives sequences of frames extracted from an RGB video stream containing pigs and uses MnasNet with a DM value of 0.5 to extract image features from pigs’ ROI identified by predefined annotations. These extracted features are then forwarded to a lightweight LSTM to learn temporal features and perform behavior recognition. The experimental results show that our proposed model achieved 0.92 in recall and F1-score with an execution time of 118.16 ms/sequence.
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| 키워드(Keyword) |
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| 파일첨부 |
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