IEEE

SACU-Net: Shape-Aware U-Net for Biomedical Image Segmentation With Attention Mechanism and Context Extraction

With the rapid development of convolutional neural networks in image processing, deep learning has been widely applied to medical image segmentation tasks, including liver, retinal vessels, nuclei, ...
IEEE

Graph U-Net With Topology-Feature Awareness Pooling for Hyperspectral Image Classification

Abstract: Nowadays, various graph convolutional networks (GCNs) to process graph-structured data have been proposed for hyperspectral image (HSI) classification. Nevertheless, most GCN-based HSI ...
GitHub

U-Net for brain segmentation

U-Net implementation in PyTorch for FLAIR abnormality segmentation in brain MRI based on a deep learning segmentation algorithm used in Association of genomic subtypes of lower-grade gliomas with ...
GitHub

Learn PyTorch for Deep Learning

Welcome to the Zero to Mastery Learn PyTorch for Deep Learning course, the second best place to learn PyTorch on the internet (the first being the PyTorch documentation). 00 - PyTorch Fundamentals ...