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Peng Li, Dezheng Zhang, Aziguli Wulamu, Xin Liu and Peng Chen
A deep understanding of our visual world is more than an isolated perception on a series of objects, and the relationships between them also contain rich semantic information. Especially for those satellite remote sensing images, the span is so large tha...
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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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Xiaoqin Lian, Xue Huang, Chao Gao, Guochun Ma, Yelan Wu, Yonggang Gong, Wenyang Guan and Jin Li
In recent years, the advancement of deep learning technology has led to excellent performance in synthetic aperture radar (SAR) automatic target recognition (ATR) technology. However, due to the interference of speckle noise, the task of classifying SAR ...
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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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Changhong Liu, Jiawen Wen, Jinshan Huang, Weiren Lin, Bochun Wu, Ning Xie and Tao Zou
Underwater object detection is crucial in marine exploration, presenting a challenging problem in computer vision due to factors like light attenuation, scattering, and background interference. Existing underwater object detection models face challenges ...
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Qiyan Li, Zhi Weng, Zhiqiang Zheng and Lixin Wang
The decrease in lake area has garnered significant attention within the global ecological community, prompting extensive research in remote sensing and computer vision to accurately segment lake areas from satellite images. However, existing image segmen...
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Yuting Chen, Pengjun Zhao, Yi Lin, Yushi Sun, Rui Chen, Ling Yu and Yu Liu
Precise identification of spatial unit functional features in the city is a pre-condition for urban planning and policy-making. However, inferring unknown attributes of urban spatial units from data mining of spatial interaction remains a challenge in ge...
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Xinzhi Wang, Mengyue Li, Quanyi Liu, Yudong Chang and Hui Zhang
The accurate analysis of multi-scale flame development plays a crucial role in improving firefighting decisions and facilitating smart city establishment. However, flames? non-rigid nature and blurred edges present challenges in achieving accurate segmen...
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Luzhou Liu, Xiaoxia Zhang, Yingwei Li and Zhinan Xu
Accurate segmentation of skin lesions is still a challenging task for automatic diagnostic systems because of the significant shape variations and blurred boundaries of the lesions. This paper proposes a multi-scale convolutional neural network, REDAUNet...
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Alyaa Amer, Tryphon Lambrou and Xujiong Ye
The advanced development of deep learning methods has recently made significant improvements in medical image segmentation. Encoder?decoder networks, such as U-Net, have addressed some of the challenges in medical image segmentation with an outstanding p...
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Chan Zeng, Junfeng Zheng and Jiangyun Li
The conveyor belt is an indispensable piece of conveying equipment for a mine whose deviation caused by roller sticky material and uneven load distribution is the most common failure during operation. In this paper, a real-time conveyor belt detection al...
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Lei Zhang and Xiaoli Zhi
Convolutional neural networks (CNN for short) have made great progress in face detection. They mostly take computation intensive networks as the backbone in order to obtain high precision, and they cannot get a good detection speed without the support of...
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Lei Zhang and Xiaoli Zhi
Convolutional neural networks (CNN for short) have made great progress in face detection. They mostly take computation intensive networks as the backbone in order to obtain high precision, and they cannot get a good detection speed without the support of...
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