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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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Minghu Wu, Chengpeng Yue, Fan Zhang, Rui Sun, Jing Tang, Sheng Hu, Nan Zhao and Juan Wang
The state of health (SOH) and remaining useful life (RUL) of lithium-ion batteries are critical indicators for assessing battery reliability and safety management. However, these two indicators are difficult to measure directly, posing a challenge to ens...
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Bo Zhao, Qifan Zhang, Yangchun Liu, Yongzhi Cui and Baixue Zhou
In response to the need for precision and intelligence in the assessment of transplanting machine operation quality, this study addresses challenges such as low accuracy and efficiency associated with manual observation and random field sampling for the ...
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Hongfeng Gao, Tiexin Xu, Renlong Li and Chaozhi Cai
Because the gearbox in transmission systems is prone to failure and the fault signal is not obvious, the fault end cannot be located. In this paper, a gearbox fault diagnosis method grounded on improved complete ensemble empirical mode decomposition with...
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Hui Deng, Wenjiang Zhang, Xiaoqian Zheng and Houxi Zhang
The accurate and timely identification of crops holds paramount significance for effective crop management and yield estimation. Unmanned aerial vehicle (UAV), with their superior spatial and temporal resolution compared to satellite-based remote sensing...
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Junsheng Liu, Guangze Zhao, Shuangxi Liu, Yi Liu, Huawei Yang, Jingwei Sun, Yinfa Yan, Guoqiang Fan, Jinxing Wang and Hongjian Zhang
In the realm of automated apple picking operations, the real-time monitoring of apple maturity and diameter characteristics is of paramount importance. Given the constraints associated with feature detection of apples in automated harvesting, this study ...
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Ching-Lung Fan
The emergence of deep learning-based classification methods has led to considerable advancements and remarkable performance in image recognition. This study introduces the Multiscale Feature Convolutional Neural Network (MSFCNN) for the extraction of com...
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Xuejing Xie, Yongyang Xu, Bin Feng and Wenjun Wu
The classification of urban functional areas is important for understanding the characteristics of urban areas and optimizing the utilization of urban land resources. Existing related methods have improved accuracy. However, they neglect cognitive differ...
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Huile Zhang, Zeyu Sun, Pengpeng Zhi, Wei Wang and Zhonglai Wang
This paper develops a material-structure integrated design and optimization method based on a multiscale approach for the lightweight design of CFRP car doors. Initially, parametric modeling of RVE is implemented, and their elastic performance parameters...
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Ping Huang and Yafeng Wu
Airborne speech enhancement is always a major challenge for the security of airborne systems. Recently, multi-objective learning technology has become one of the mainstream methods of monaural speech enhancement. In this paper, we propose a novel multi-o...
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