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1篇 您的检索式：作者名="XueLian Mu"

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		题名	作者	年代	出处	被引量
	1	Channel Context and Dual-Domain Attention Based U-Net for Skin Lesion Attributes Segmentation显示文摘Skin melanoma is one of the most common malignant tumorsoriginating from melanocytes, and the incidence of the Chinese populationis showing a continuous increasing trend. Early and accurate diagnosisof melanoma has great significance for guiding clinical treatment.However, the symptoms of malignant melanoma are not obvious in theearly stage. It is difficult to be diagnosed with human observation. Meanwhile,it is easy to spread due to missed diagnosis. In order to accuratelydiagnose melanoma, end-to-end skin lesion attribute segmentation frameworkis presented in this paper. It is applied to facilitate the digitalizationprocess of attributes segmentation. The framework was improved on theU-Net construction that use the channel context feature fusion modulebetween the encoder and decoder to further merge context information. Adual-domain attention module is proposed to get more effective informationfrom the feature map. It shows that the proposed method effectivelysegments the lesion attributes and achieves good result in the ISIC2018task2 dataset.	XueLian Mu HaiWei Pan KeJia Zhang Teng Teng XiaoFei Bian ChunLing Chen	2021	国际计算机前沿大会会议论文集2021，，1：	0

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