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[SG-UNet:用全球关注和自我校准卷积增强的黑色素瘤细分模型]

Huanyu Ji1, Rui Wang2, Shengxiang Gao1,3

  • 1Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China.

Nan fang yi ke da xue xue bao = Journal of Southern Medical University
|June 27, 2025
PubMed
概括

新的SG-UNet模型显著改善了皮肤镜图像中的黑色素瘤细分,提高了早期检测. 这种深度学习方法改进了特征提取和上下文理解,以获得更精确的结果.

关键词:
哈尔波束下方采样 下方采样总书记 - 联合国网联合国网络 联合国网络 联合国网络全球关注机制全球关注机制图像分割 图像细分 图像细分黑色素瘤是一种黑色素瘤.自行校准的卷积卷积.

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