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Haiping Si, Mingchun Li, Weixia Li, Guipei Zhang, Ming Wang, Feitao Li and Yanling Li
Apples, as the fourth-largest globally produced fruit, play a crucial role in modern agriculture. However, accurately identifying apple diseases remains a significant challenge as failure in this regard leads to economic losses and poses threats to food ...
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Hexin Lu, Xiaodong Zhu, Jingwei Cui and Haifeng Jiang
The process of iris recognition can result in a decline in recognition performance when the resolution of the iris images is insufficient. In this study, a super-resolution model for iris images, namely SwinGIris, which combines the Swin Transformer and ...
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Jie Zhang, Fan Li, Xin Zhang, Yue Cheng and Xinhong Hei
As a crucial task for disease diagnosis, existing semi-supervised segmentation approaches process labeled and unlabeled data separately, ignoring the relationships between them, thereby limiting further performance improvements. In this work, we introduc...
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Guoqing Dong, Weirong Li, Zhenzhen Dong, Cai Wang, Shihao Qian, Tianyang Zhang, Xueling Ma, Lu Zou, Keze Lin and Zhaoxia Liu
The developed prototype provides a more efficient and accurate solution for classifying dynagraph cards, meeting the requirements of oil field operations and enhancing economic benefits and work efficiency.
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Hao Gu, Ming Chen and Dongmei Gan
The identification of gender in Chinese mitten crab juveniles is a critical prerequisite for the automatic classification of these crab juveniles. Aiming at the problem that crab juveniles are of different sizes and relatively small, with unclear male an...
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Zhendong He, Wenbin Yang, Yanjie Liu, Anping Zheng, Jie Liu, Taishan Lou and Jie Zhang
Ensuring the safety of transmission lines necessitates effective insulator defect detection. Traditional methods often need more efficiency and accuracy, particularly for tiny defects. This paper proposes an innovative insulator defect recognition method...
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Chenglin Yang, Dongliang Xu and Xiao Ma
Due to the increasing severity of network security issues, training corresponding detection models requires large datasets. In this work, we propose a novel method based on generative adversarial networks to synthesize network data traffic. We introduced...
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Minghao Liu, Qingxi Luo, Jianxiang Wang, Lingbo Sun, Tingting Xu and Enming Wang
Land use/cover change (LUCC) refers to the phenomenon of changes in the Earth?s surface over time. Accurate prediction of LUCC is crucial for guiding policy formulation and resource management, contributing to the sustainable use of land, and maintaining...
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Zhe Yin, Mingkang Peng, Zhaodong Guo, Yue Zhao, Yaoyu Li, Wuping Zhang, Fuzhong Li and Xiaohong Guo
With the advancement of machine vision technology, pig face recognition has garnered significant attention as a key component in the establishment of precision breeding models. In order to explore non-contact individual pig recognition, this study propos...
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Minghui Sha, Dewu Wang, Fei Meng, Wenyan Wang and Yu Han
With the increasing complexity of radar jamming threats, accurate and automatic jamming recognition is essential but remains challenging. Conventional algorithms often suffer from sharply decreased recognition accuracy under low jamming-to-noise ratios (...
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