Adversarial learning with multi-scale loss for skin lesion segmentation
簡介 這是一個端到端的對抗神經網絡，即SegAN。generator是一個全卷積網絡，並使用了一種新的激活函數。discriminator使用一個多層 L1 L 1 損失(multi-scale L1 L 1 loss)，segmentor通過長或短範圍的像素空間關係來學習全局和局部特徵。使用的數據是ISIC2017(International Skin Imaging Collaboration
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相關文章
- 1. Improving Lesion Segmentation for Diabetic Retinopathy using Adversarial Learning
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