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Zhou Fang, Xiaoyong Wang, Liang Zhang and Bo Jiang
Currently, deep learning is extensively utilized for ship target detection; however, achieving accurate and real-time detection of multi-scale targets remains a significant challenge. Considering the diverse scenes, varied scales, and complex backgrounds...
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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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Jingxiong Lei, Xuzhi Liu, Haolang Yang, Zeyu Zeng and Jun Feng
High-resolution remote sensing images (HRRSI) have important theoretical and practical value in urban planning. However, current segmentation methods often struggle with issues like blurred edges and loss of detailed information due to the intricate back...
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Jiaming Bian, Ye Liu and Jun Chen
In recent times, remote sensing image super-resolution reconstruction technology based on deep learning has experienced rapid development. However, most algorithms in this domain concentrate solely on enhancing the super-resolution network?s performance ...
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Hang Li, Shengjie Zhao and Hao Deng
The extraction of community-scale green infrastructure (CSGI) poses challenges due to limited training data and the diverse scales of the targets. In this paper, we reannotate a training dataset of CSGI and propose a three-stage transfer learning method ...
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Enzhan Zhang, Liang Li, Weiche Huang, Yucheng Jia, Minghu Zhang, Faming Kang and Hu Da
Large-scale particle image velocimetry (LSPIV) is a computer vision-based technique renowned for its precise and efficient measurement of river surface velocity. However, a crucial prerequisite for utilizing LSPIV involves camera calibration. Conventiona...
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Fadi Shaar, Arif Yilmaz, Ahmet Ercan Topcu and Yehia Ibrahim Alzoubi
Recognizing aircraft automatically by using satellite images has different applications in both the civil and military sectors. However, due to the complexity and variety of the foreground and background of the analyzed images, it remains challenging to ...
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Zhixin Li, Song Ji, Dazhao Fan, Zhen Yan, Fengyi Wang and Ren Wang
Accurate building geometry information is crucial for urban planning in constrained spaces, fueling the growing demand for large-scale, high-precision 3D city modeling. Traditional methods like oblique photogrammetry and LiDAR prove time consuming and ex...
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Peng Zhang, Qin Qin, Shijie Zhang, Xiangtian Zhao, Xiaoliang Yan, Wei Wang and Hongbin Zhang
Remote sensing has become an essential tool for geological exploration, disaster monitoring, emergency rescue, and environmental supervision, while the limited number of remote sensing satellites and ground stations restricts the timeliness of remote sen...
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Ruoyang Li, Shuping Xiong, Yinchao Che, Lei Shi, Xinming Ma and Lei Xi
Semantic segmentation algorithms leveraging deep convolutional neural networks often encounter challenges due to their extensive parameters, high computational complexity, and slow execution. To address these issues, we introduce a semantic segmentation ...
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