Zobrazeno 1 - 10
of 85
pro vyhledávání: '"BIFormer"'
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
IntroductionThe detection efficiency of tea diseases and defects ensures the quality and yield of tea. However, in actual production, on the one hand, the tea plantation has high mountains and long roads, and the safety of inspection personnel cannot
Externí odkaz:
https://doaj.org/article/918d3687884e49d98cda5ef60867fcae
Publikováno v:
Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)
Abstract The automated replacement of empty tubes in the yarn bank is a critical step in the process of automatic winding machines with yarn banks, as the real-time detection of depleted yarn on spools and accurate positioning of empty tubes directly
Externí odkaz:
https://doaj.org/article/dc416969cb894efe96b918064fea3e38
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
The detection of apple leaf diseases plays a crucial role in ensuring crop health and yield. However, due to variations in lighting and shadow, as well as the complex relationships between perceptual fields and target scales, current detection method
Externí odkaz:
https://doaj.org/article/c103107fd0c94278ae891e72816500ce
Publikováno v:
AIMS Mathematics, Vol 9, Iss 5, Pp 10775-10801 (2024)
Fire is a common but serious disaster, which poses a great threat to human life and property. Therefore, fire-smoke detection technology is of great significance in various fields. In order to improve the detection ability of tiny-fire, so as to real
Externí odkaz:
https://doaj.org/article/4658cbd927904625ba5f12fd3474ee19
Autor:
Fuqin Deng, Jianle Chen, Lanhui Fu, Jiaming Zhong, Weilai Qiaoi, Jialong Luo, Junwei Li, Nannan Li
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
Variety detection provides technical support for selecting XinHui citrus for use in the production of XinHui dried tangerine peel. Simultaneously, the mutual occlusion between tree leaves and fruits is one of the challenges in object detection. In or
Externí odkaz:
https://doaj.org/article/129fd1762a9741e88ca496f61f374454
Publikováno v:
IEEE Access, Vol 12, Pp 140809-140822 (2024)
Aiming at the YOLO (You Only Look Once) algorithm’s low detection accuracy caused by the complex background environment and large target scale difference in optical remote sensing image detection, the lightweight convolution fusion attention mechan
Externí odkaz:
https://doaj.org/article/c3cb9830801642858cd9b9e6dd312aad
Autor:
Zejun Wang, Shihao Zhang, Lijiao Chen, Wendou Wu, Houqiao Wang, Xiaohui Liu, Zongpei Fan, Baijuan Wang
Publikováno v:
Agriculture, Vol 14, Iss 10, p 1739 (2024)
Pest infestations in tea gardens are one of the common issues encountered during tea cultivation. This study introduces an improved YOLOv8 network model for the detection of tea pests to facilitate the rapid and accurate identification of early-stage
Externí odkaz:
https://doaj.org/article/a82b2d8e255144a4ad81d0777694602f
Publikováno v:
Agronomy, Vol 14, Iss 5, p 1034 (2024)
Pest target identification in agricultural production environments is challenging due to the dense distribution, small size, and high density of pests. Additionally, changeable environmental lighting and complex backgrounds further complicate the det
Externí odkaz:
https://doaj.org/article/bddea285f5984d1eba8daee3e6b7a053
Publikováno v:
World Electric Vehicle Journal, Vol 15, Iss 3, p 102 (2024)
Pavement defect detection technology stands as a pivotal component within intelligent driving systems, demanding heightened precision and rapid detection rates. Addressing the complexities arising from diverse defect types and intricate backgrounds i
Externí odkaz:
https://doaj.org/article/fcb5ed1695044b29885bd0fd428fb617
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