扫兴
发表于 2025-3-30 08:41:18
A Style Transfer-Based Augmentation Framework for Improving Segmentation and Classification Performam the style of a training image into various reference styles, which enriches the information from different sources for the network. FeatAug augments the styles at the feature level to compensate for possible style variations, especially for small-size datasets with limited styles. MaskAug leverage
裤子
发表于 2025-3-30 13:47:30
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的事物
发表于 2025-3-30 19:18:53
SegNetr: Rethinking the Local-Global Interactions and Skip Connections in U-Shaped Networksial location information of encoder features and achieve accurate fusion with the decoder features. We validate the effectiveness of SegNetr on four mainstream medical image segmentation datasets, with 59% and 76% fewer parameters and GFLOPs than vanilla U-Net, while achieving segmentation performan
撕裂皮肉
发表于 2025-3-30 21:25:21
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rectocele
发表于 2025-3-31 01:59:10
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厨师
发表于 2025-3-31 07:39:11
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LEVER
发表于 2025-3-31 10:43:49
Frequency-Mixed Single-Source Domain Generalization for Medical Image Segmentation constructed in the domain augmentation to learn robust context-aware representations for the segmentation task. Experimental results on five datasets of three modalities demonstrate the effectiveness of the proposed algorithm. FreeSDG outperforms state-of-the-art methods and significantly improves
简略
发表于 2025-3-31 15:09:30
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