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Xin Chen, Peng Shi and Yi Hu
Semantic segmentation methods have been successfully applied in seabed sediment detection. However, fast models like YOLO only produce rough segmentation boundaries (rectangles), while precise models like U-Net require too much time. In order to achieve ...
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Lingfeng Huang, Jieyu Zhao and Yu Chen
3D mesh as a complex data structure can provide effective shape representation for 3D objects, but due to the irregularity and disorder of the mesh data, it is difficult for convolutional neural networks to be directly applied to 3D mesh data processing....
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Yunzhuo Liu, Chunjiang Wu, Yuting Zeng, Keyu Chen and Shijie Zhou
Artificial Intelligence has been widely applied in intelligent transportation systems. In this work, Swin-APT, a deep learning-based approach for semantic segmentation and object detection in intelligent transportation systems is presented. Swin-APT incl...
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Rongke Wei, Anyang Song, Huixian Duan and Haodong Pei
With the development of space technology, deep learning methods, with their excellent generalization ability, are increasingly applied in various space activities. The space object data is difficult to obtain, which greatly limits its application in spac...
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Semen Mukhamadiev, Sergey Nesteruk, Svetlana Illarionova and Andrey Somov
Plant segmentation is a challenging computer vision task due to plant images complexity. For many practical problems, we have to solve even more difficult tasks. We need to distinguish plant parts rather than the whole plant. The major complication of mu...
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