Showing 1-11 of 11 projects
A PyTorch implementation of the U-Net for image semantic segmentation with high quality images.
A Jupyter Notebook implementation of the U-Net convolutional neural network for image segmentation tasks.
Efficient 3D U-Net model for volumetric semantic segmentation of medical images, built with PyTorch.
This is a PyTorch implementation of a 3D U-Net CNN for medical image segmentation.
A simple implementation of the Denoising Diffusion Probability Model (DDPM) for training a U-Net on the CIFAR-10 dataset.
A generic U-Net implementation in TensorFlow for image segmentation tasks.
An open-source library for efficient diffusion models in computer vision, with potential AI coding tool applications.
This is the source code for a PyTorch implementation of the U-Net model, which can be used to train custom models.
A library of code samples and examples for deep learning and computer vision, targeting beginners.
A toolbox for training and deploying object detectors and segmentation models on medical images using PyTorch.
A PyTorch implementation of the UNet++ (Nested U-Net) architecture for image segmentation tasks.
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