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U-Net implementation in PyTorch for FLAIR abnormality segmentation in brain MRI
Vnet is a PyTorch implementation of the paper V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation by Fausto Milletari, Nassir Navab, and Seyed-Ahmad Ahmadi. Although this implementation is still a work in progress, I'm seeing a respectable 0.355% test error rate…
This repository provides structured code examples and project templates designed for classroom instruction in machine learning and neural networks. It offers reference implementations of deep learning models for both computer vision and natural language processing tasks, built using PyTorch as the core framework. The codebase is organized as a modular project template with separate directories for data handling, model definitions, and training scripts, promoting reusability and clarity. It includes predefined pipelines for image classification and text processing, along with a command-line in
A PyTorch implementation of "DGC-Net: Dense Geometric Correspondence Network"
🚨 Paper now online! https://arxiv.org/abs/2111.00595
The main features of mlmed/torchxrayvision are: Computer Vision Models, Medical.
Open-source alternatives to mlmed/torchxrayvision include: mattmacy/vnet.pytorch — Vnet is a PyTorch implementation of the paper V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image… mateuszbuda/brain-segmentation-pytorch — U-Net implementation in PyTorch for FLAIR abnormality segmentation in brain MRI. cs230-stanford/cs230-code-examples — This repository provides structured code examples and project templates designed for classroom instruction in machine… aaltovision/dgc-net — A PyTorch implementation of "DGC-Net: Dense Geometric Correspondence Network". alaphao/coremlexample — An example of CoreML using a pre-trained VGG16 model. adamian98/pulse — Pulse is a generative model image upscaler and latent space image processor. It functions as a self-supervised photo…