Progressive Resolution Reduction With Feature Dimension Expansion

* ⭐ 07/2022: [Swin UNETR: Swin Transformers for Semantic Segmentation of Brain Tumors... (Swin UNETR)](https://link.springer.com/chapter/10.1007/978-3-031-08999-2_22)

Unique: Combines CNN-style progressive resolution reduction with Transformer-style feature expansion in a principled way, using patch merging operations that apply grouped convolutions to merge 2×2 spatial patches into single tokens while expanding channels. This maintains the efficiency benefits of both paradigms while enabling smooth integration of CNN and Transformer components.