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Yu-Ting Tsai and Ching-Piao Tsai
Deep learning techniques have revolutionized the field of artificial intelligence by enabling accurate predictions of complex natural scenarios. This paper proposes a novel convolutional neural network (CNN) model that involves deep learning technologies...
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Yulong Liu, Shuxian Liu and Juepu Chen
Accurate precipitation forecasting is of great significance to social life and economic activities. Due to the influence of various factors such as topography, climate, and altitude, the precipitation in semi-arid and arid areas shows the characteristics...
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Hao Wang, Lixin Zhang, Huan Wang, Xue Hu, Jiawei Zhao, Fenglei Zhu and Xun Wu
Xinjiang is the largest cotton-producing region in China, but it faces a severe shortage of water resources. According to relevant studies, the cotton yield does not significantly decrease under appropriate limited water conditions. Therefore, this paper...
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Shengping Wen, Yue Yuan and Jingfu Chen
The preliminary sorting of plastic products is a necessary step to improve the utilization of waste resources. To improve the quality and efficiency of sorting, a plastic detection scheme based on deep learning is proposed in this paper for a waste plast...
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Elena Martínez-Fernandez, Ignacio Rojas-Valenzuela, Olga Valenzuela and Ignacio Rojas
The diagnosis of different pathologies and stages of cancer using whole histopathology slide images (WSI) is the gold standard for determining the degree of tissue metastasis. The use of deep learning systems in the field of medical images, especially hi...
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Linjing Hu, Jiachen Wang, Zhaoze Guo and Tengda Zheng
Power load forecasting plays an important role in power systems, and the accuracy of load forecasting is of vital importance to power system planning as well as economic efficiency. Power load data are nonsmooth, nonlinear time-series and ?noisy? data. T...
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Hechao Ye and Yanni Wang
Crowding and occlusion pose significant challenges for pedestrian detection, which can easily lead to missed and false detections for small-scale and occluded pedestrian objects in dense pedestrian scenarios. To enhance dense pedestrian detection accurac...
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Rina Komatsu and Tad Gonsalves
In CycleGAN, an image-to-image translation architecture was established without the use of paired datasets by employing both adversarial and cycle consistency loss. The success of CycleGAN was followed by numerous studies that proposed new translation mo...
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Qingbin Tong, Feiyu Lu, Ziwei Feng, Qingzhu Wan, Guoping An, Junci Cao and Tao Guo
The data-driven intelligent fault diagnosis method of rolling bearings has strict requirements regarding the number and balance of fault samples. However, in practical engineering application scenarios, mechanical equipment is usually in a normal state, ...
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Wenyi Zhou, Hongguang Fan, Jihong Zhu, Hui Wen and Ying Xie
This paper first studies the generalization ability of the convolutional layer as a feature mapper (CFM) for extracting image features and the classification ability of the multilayer perception (MLP) in a CNN. Then, a novel generalized hybrid probabilit...
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