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NAS-Unet: Neural Architecture Search for Medical Image Segmentation
Neural architecture search (NAS) has significant progress in improving the accuracy of image classification. Recently, some works attempt to extend NAS to image segmentation which shows preliminary feasibility. However, all of them focus on searching architecture for semantic segmentation in natural scenes. In this paper, we design three types of primitive operation set on search space to automatically find two cell architecture DownSC and UpSC for semantic image segmentation especially medicaldoi:10.1109/access.2019.2908991 fatcat:cw5knncj3fecxhbyeatplyj4ry