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Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Pytorch implementation of convolutional neural network visualization techniques
StarGAN v2 - Official PyTorch Implementation (CVPR 2020)
Research Framework for easy and efficient training of GANs based on Pytorch
🤖 PaddleViT: State-of-the-art Visual Transformer and MLP Models for PaddlePaddle 2.0+
PyTorch re-implementation of Grad-CAM (+ vanilla/guided backpropagation, deconvnet, and occlusion sensitivity maps)
[ICCV 2023] CLIP-Driven Universal Model; Rank first in MSD Competition.
Tool for onnx->keras or onnx->tflite. Hope this tool can help you.
MeshNet: Mesh Neural Network for 3D Shape Representation (AAAI 2019)
SegAN: Semantic Segmentation with Adversarial Learning
Development and validation of an interpretable deep learning framework for Alzheimer's disease classification
COVID deterioration prediction based on chest X-ray radiographs via MoCo-trained image representations
Public repo for the ICCV2021-CVAMD paper "Is it Time to Replace CNNs with Transformers for Medical Images?"
A project to provide custom sorting and renaming of dicom files
Convolutional AutoEncoder application on MRI images
unofficial implementation of paper Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder (MemAE) for Unsupervised Anomaly Detection
Kidney Tumor Segmentation Challenge 2019
Code for 'Constrained Contrastive Distribution Learning for Unsupervised Anomaly Detection and Localisation in Medical Images' [MICCAI 2021]
Convert binary map to mesh. The binary map is in nifti format and the mesh is in stl file type.
MR下肝脏和肾脏(左、右)的分割，给公司做的，pytorch
[RedJournal2023]Comprehensive evaluation of a deep learning model for automatic organs at risk segmentation on heterogeneous computed tomography images for abdominal radiotherapy.
An implementation of Deviation Network with a case on the credit card fraud dataset.