Zobrazeno 1 - 10
of 64
pro vyhledávání: '"Pig detection"'
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-10 (2024)
Abstract Object detector based on fully convolutional network achieves excellent performance. However, existing detection algorithms still face challenges such as low detection accuracy in dense scenes and issues with occlusion of dense targets. To a
Externí odkaz:
https://doaj.org/article/5f96b86af0054f5090830174942e7da9
Publikováno v:
Systems Science & Control Engineering, Vol 12, Iss 1 (2024)
Accurate and efficient livestock detection and counting are crucial for agricultural intelligence. To address the obstacles created by traditional manual methods and limitations of current vision technology, we introduce YOLOv5-MHSA-DS, a novel model
Externí odkaz:
https://doaj.org/article/02730eb5595b4460b43305baa4b4a632
Publikováno v:
Agriculture, Vol 14, Iss 10, p 1807 (2024)
Pigs play vital roles in the food supply, economic development, agricultural recycling, bioenergy, and social culture. Pork serves as a primary meat source and holds extensive applications in various dietary cultures, making pigs indispensable to hum
Externí odkaz:
https://doaj.org/article/a9b695edf56d48dbbf49f571baa65f3e
Akademický článek
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Akademický článek
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Publikováno v:
Animals, Vol 13, Iss 15, p 2472 (2023)
This paper proposes a method for automatic pig detection and segmentation using RGB-D data for precision livestock farming. The proposed method combines the enhanced YOLOv5s model with the Res2Net bottleneck structure, resulting in improved fine-grai
Externí odkaz:
https://doaj.org/article/8f8903e9d7a241e4bb397a6f6ac13e83
Publikováno v:
Sensors, Vol 22, Iss 22, p 8792 (2022)
Pork is the most widely consumed meat product in the world, and achieving accurate detection of individual pigs is of great significance for intelligent pig breeding and health monitoring. Improved pig detection has important implications for improvi
Externí odkaz:
https://doaj.org/article/f45341df5a34483e93f251528ca12792
Autor:
Seungwook Son, Hanse Ahn, Hwapyeong Baek, Seunghyun Yu, Yooil Suh, Sungju Lee, Yongwha Chung, Daihee Park
Publikováno v:
Sensors, Vol 22, Iss 21, p 8315 (2022)
The automatic detection of individual pigs can improve the overall management of pig farms. The accuracy of single-image object detection has significantly improved over the years with advancements in deep learning techniques. However, differences in
Externí odkaz:
https://doaj.org/article/68c8c5bba0e849e19d85938d396f2a85
Publikováno v:
Sensors, Vol 22, Iss 17, p 6541 (2022)
Pork accounts for an important proportion of livestock products. For pig farming, a lot of manpower, material resources and time are required to monitor pig health and welfare. As the number of pigs in farming increases, the continued use of traditio
Externí odkaz:
https://doaj.org/article/4f2c2d445aba4c19b33d54dd38a58af3
Publikováno v:
Sensors, Vol 22, Iss 10, p 3917 (2022)
Infrared cameras allow non-invasive and 24 h continuous monitoring. Thus, they are widely used in automatic pig monitoring, which is essential to maintain the profitability and sustainability of intensive pig farms. However, in practice, impurities s
Externí odkaz:
https://doaj.org/article/e80c58d625f849b8a2c29a9d6e2d901b