Swin-Unet [29] is a pure Transformer network structure, where the encoder and decoders are composed of Transformers. However, Swin-Unet is a model for 2D medical image segmentation, which is not applicable to voxel segmentation of 3D medical images unless a lot of additional work has been ...
SwinUNet3D -- A Hierarchical Architecture for Deep Traffic Prediction using Shifted Window Transformers 来自 arXiv.org 喜欢 0 阅读量: 454 作者:A Bojesomo,HA Marzouqi,P Liatsis 摘要: Traffic forecasting is an important element of mobility management, an important key that drives the logistics ...
SWIN-Unet: A Vision Transformer Based U-Net. SWIN-Unet is a novel architecture for image segmentation that combines the strengths of the Swin Transformer and U-Net. It leverages the powerful representation capabilities of the Swin Transformer and the efficient encoder-decoder structure of U-Net ...
swin-unet 英文回答: The code structure of Swin-Unet can be explained as follows: 1. Model Architecture: The Swin-Unet model is based on the U-Net architecture, which consists of an encoder and a decoder. The encoder part is responsible for extracting features from the input image, while ...
The code can be found athttps://github.com/1152545264/SwinUnet3D.doi:10.1186/s12911-023-02129-zYimin CaiYuqing LongZhenggong HanMing-Chang LiuYuchen ZhengWei YangLiming ChenBioMed CentralBMC Medical Informatics and Decision Making
In this paper, motivative by Swin Transformer, we proposed BTSwin-Unet, which is a 3D U-shaped symmetrical Swin Transformer-based network for brain tumor segmentation. Moreover, we construct a self-supervised learning framework to pre-train the model encoder through the reconstruction task. ...
In this paper, motivative by Swin Transformer, we proposed BTSwin-Unet, which is a 3D U-shaped symmetrical Swin Transformer-based network for brain tumor segmentation. Moreover, we construct a self-supervised learning framework to pre-train the model encoder through the reconstruction task. ...