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Zhichao Chen, Hongping Zhou, Haifeng Lin and Di Bai
The tea industry, as one of the most globally important agricultural products, is characterized by pests and diseases that pose a serious threat to yield and quality. These diseases and pests often present different scales and morphologies, and some pest...
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Xuejun Yue, Haifeng Li, Qingkui Song, Fanguo Zeng, Jianyu Zheng, Ziyu Ding, Gaobi Kang, Yulin Cai, Yongda Lin, Xiaowan Xu and Chaoran Yu
Existing disease detection models for deep learning-based monitoring and prevention of pepper diseases face challenges in accurately identifying and preventing diseases due to inter-crop occlusion and various complex backgrounds. To address this issue, w...
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Huiwen Ji, Min Xia, Dongsheng Zhang and Haifeng Lin
Cloud and cloud shadow detection are essential in remote sensing imagery applications. Few semantic segmentation models were designed specifically for clouds and their shadows. Based on the visual and distribution characteristics of clouds and their shad...
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Lide Wei, Zhinan Lin, Haifeng Long and Qiongyao Ye
In order to investigate the mechanical properties and permeability characteristics of sandstone during damage evolution under hydromechanical condition, a series of coupled hydro-mechanical triaxial tests on sandstone specimens were conducted based on th...
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Chaoyun Yang, Yonghong Zhang, Min Xia, Haifeng Lin, Jia Liu and Yang Li
Cloud and snow recognition technology is of great significance in the field of meteorology, and is also widely used in remote sensing mapping, aerospace, and other fields. Based on the traditional method of manually labeling cloud-snow areas, a method of...
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Cheng Ding, Liguo Weng, Min Xia and Haifeng Lin
Building and road extraction from remote sensing images is of great significance to urban planning. At present, most of building and road extraction models adopt deep learning semantic segmentation method. However, the existing semantic segmentation meth...
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Hongjian Bo, Haifeng Li, Boying Wu, Hongwei Li and Lin Ma
At present, there are very few analysis methods for long-term electroencephalogram (EEG) components. Temporal information is always ignored by most of the existing techniques in cognitive studies. Therefore, a new analysis method based on time-varying ch...
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Santosh Kumar Banbhrani, Bo Xu, Haifeng Liu and Hongfei Lin
Hashtags are considered important in various real-world applications, including tweet mining, query expansion, and sentiment analysis. Hence, recommending hashtags from tagged tweets has been considered significant by the research community. However, whi...
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Shang Feng, Haifeng Li, Lin Ma and Zhongliang Xu
In the application of the brain-computer interface, feature extraction is an important part of Electroencephalography (EEG) signal classification. Using sparse modeling to extract EEG signal features is a common approach. However, the features extracted ...
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Chang Lin, Wu Chen and Haifeng Zhou
To visually detect sea-surface targets, the objects of interest must be effectively and rapidly isolated from the background of sea-surface images. In contrast to traditional image detection methods, which employ a single visual feature, this paper propo...
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