Identification and Analysis of Emergency Behavior of Cage-Reared Laying Ducks Based on YoloV5
The behavior of cage-reared ducks is an important index to judge the health status of laying ducks. For the automatic recognition task of cage-reared duck behavior based on machine vision, by comparing the detection performance of YoloV4 (you only look once), YoloV5, and Faster-RCNN, this work selec...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Agriculture |
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| Online Access: | https://www.mdpi.com/2077-0472/12/4/485 |
| _version_ | 1797437345183563776 |
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| author | Yue Gu Shucai Wang Yu Yan Shijie Tang Shida Zhao |
| author_facet | Yue Gu Shucai Wang Yu Yan Shijie Tang Shida Zhao |
| author_sort | Yue Gu |
| collection | DOAJ |
| description | The behavior of cage-reared ducks is an important index to judge the health status of laying ducks. For the automatic recognition task of cage-reared duck behavior based on machine vision, by comparing the detection performance of YoloV4 (you only look once), YoloV5, and Faster-RCNN, this work selected the YoloV5 target detection network with the best performance to identify the three behaviors related to avoidance after a cage-reared duck emergency. The recognition average precision was 98.2% (neck extension), 98.5% (trample), and 98.6% (spreading wings), respectively, and the detection speed was 20.7 FPS. Based on this model, in this work, 10 duck cages were randomly selected, and each duck cage recorded video for 3 min when there were breeders walking in the duck house and no one was walking for more than 20 min. By identifying the generation time and frequency of neck extension out of the cage, trample, and wing spread, it was concluded that the neck extension, trampling, and wing spread behaviors of laying ducks increase significantly when they feel panic and fear. The research provides an efficient, intelligent monitoring method for the behavior analysis of cage-rearing of ducks and provides a basis for the health status judgment and behavior analysis of unmonitored laying ducks in the future. |
| first_indexed | 2024-03-09T11:18:52Z |
| format | Article |
| id | doaj.art-1afbc641beff4a33a5c0c1858647776a |
| institution | Directory Open Access Journal |
| issn | 2077-0472 |
| language | English |
| last_indexed | 2024-03-09T11:18:52Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Agriculture |
| spelling | doaj.art-1afbc641beff4a33a5c0c1858647776a2023-12-01T00:23:54ZengMDPI AGAgriculture2077-04722022-03-0112448510.3390/agriculture12040485Identification and Analysis of Emergency Behavior of Cage-Reared Laying Ducks Based on YoloV5Yue Gu0Shucai Wang1Yu Yan2Shijie Tang3Shida Zhao4College of Engineering, Huazhong Agricultural University, Wuhan 430070, ChinaCollege of Engineering, Huazhong Agricultural University, Wuhan 430070, ChinaCollege of Engineering, Huazhong Agricultural University, Wuhan 430070, ChinaCollege of Engineering, Huazhong Agricultural University, Wuhan 430070, ChinaCollege of Engineering, Huazhong Agricultural University, Wuhan 430070, ChinaThe behavior of cage-reared ducks is an important index to judge the health status of laying ducks. For the automatic recognition task of cage-reared duck behavior based on machine vision, by comparing the detection performance of YoloV4 (you only look once), YoloV5, and Faster-RCNN, this work selected the YoloV5 target detection network with the best performance to identify the three behaviors related to avoidance after a cage-reared duck emergency. The recognition average precision was 98.2% (neck extension), 98.5% (trample), and 98.6% (spreading wings), respectively, and the detection speed was 20.7 FPS. Based on this model, in this work, 10 duck cages were randomly selected, and each duck cage recorded video for 3 min when there were breeders walking in the duck house and no one was walking for more than 20 min. By identifying the generation time and frequency of neck extension out of the cage, trample, and wing spread, it was concluded that the neck extension, trampling, and wing spread behaviors of laying ducks increase significantly when they feel panic and fear. The research provides an efficient, intelligent monitoring method for the behavior analysis of cage-rearing of ducks and provides a basis for the health status judgment and behavior analysis of unmonitored laying ducks in the future.https://www.mdpi.com/2077-0472/12/4/485behavior identificationcage-reared ducksdeep learningYoloV5 |
| spellingShingle | Yue Gu Shucai Wang Yu Yan Shijie Tang Shida Zhao Identification and Analysis of Emergency Behavior of Cage-Reared Laying Ducks Based on YoloV5 Agriculture behavior identification cage-reared ducks deep learning YoloV5 |
| title | Identification and Analysis of Emergency Behavior of Cage-Reared Laying Ducks Based on YoloV5 |
| title_full | Identification and Analysis of Emergency Behavior of Cage-Reared Laying Ducks Based on YoloV5 |
| title_fullStr | Identification and Analysis of Emergency Behavior of Cage-Reared Laying Ducks Based on YoloV5 |
| title_full_unstemmed | Identification and Analysis of Emergency Behavior of Cage-Reared Laying Ducks Based on YoloV5 |
| title_short | Identification and Analysis of Emergency Behavior of Cage-Reared Laying Ducks Based on YoloV5 |
| title_sort | identification and analysis of emergency behavior of cage reared laying ducks based on yolov5 |
| topic | behavior identification cage-reared ducks deep learning YoloV5 |
| url | https://www.mdpi.com/2077-0472/12/4/485 |
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