Efficient and accurate detection of herd pigs based on Ghost-YOLOv7-SIoU-Reference-Cited by-同舟云学术

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Efficient and accurate detection of herd pigs based on Ghost-YOLOv7-SIoU

Published:2023-10-24 Issue:5 Volume:36 Page:2339-2352
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Sun Donglai,Zhang Lijuan,Wang Jianqiang,Liu Xintong,Wang Zhengbo,Hui Zhenqiao,Wang Jichao

Funder

Science and Technology Project of Hebei Education Department

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-023-09093-9.pdf

Reference36 articles.

1. Maselyne J, Saeys W, De Ketelaere B et al (2014) Validation of a high frequency radio frequency identification (HF RFID) system for registering feeding patterns of growing-finishing pigs. Comput Electron Agric 102:10–18

2. Guo Y, Zhu W, Jiao P et al (2014) Foreground detection of group-housed pigs based on the combination of Mixture of Gaussians using prediction mechanism and threshold segmentation. Biosys Eng 125:98–104

3. Yiyang L, Longqing S, Yuanbing Z et al (2017) Individual pig object detection algorithm based on Gaussian mixture model. Int J Agric Biol Eng 10(5):186–193

4. Huang W, Zhu W, Ma C et al (2018) Identification of group-housed pigs based on gabor and local binary pattern features. Biosys Eng 166:90–100

5. Huang W, Zhu W, Ma C et al (2020) Weber texture local descriptor for identification of group-housed pigs. Sensors 20(16):4649

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