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Name: Jesse Liu
Type: User
Bio: Student
Name: Jesse Liu
Type: User
Bio: Student
Code for the paper "Contrastive Clustering" (AAAI 2021)
Unet2d for brats segmentation.
Pytorch implementation of the paper "3D MRI brain tumor segmentation using autoencoder regularization" by Myronenko A. [https://arxiv.org/abs/1810.11654]
Fast image augmentation library and an easy-to-use wrapper around other libraries. Documentation: https://albumentations.ai/docs/ Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
A module for 3D image augmentations for deep learning, specifically medical images such as CT, MRI.
A curated list of awesome self-supervised methods
PyTorch & Keras implementation for BraTs (Brain Tumor Segmentation)
3d unet + vae, repoduce brats2018 winner solution
Deep Clustering for Unsupervised Learning of Visual Features
Experiments for understanding disentanglement in VAE latent representations
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
More readable and flexible yolov5 with more backbone(resnet, shufflenet, moblienet )
Config files for my GitHub profile.
Converts medical images to more displayable formats, e.g. NIfTI to jpg.
The Medical Detection Toolkit contains 2D + 3D implementations of prevalent object detectors such as Mask R-CNN, Retina Net, Retina U-Net, as well as a training and inference framework focused on dealing with medical images.
Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection (MemAE)
Memory-augmented Deep Autoencoder (https://arxiv.org/abs/1904.02639) for Vector Data
Pixel-Adaptive Convolutional Neural Networks (CVPR '19)
在投图象图形学报论文的代码
Implementation of the paper Self-Supervised Learning of Pretext-Invariant Representations
‘‘R2D2-GAN: Robust Dual-Discriminator Generative Adversarial Network for Microscopy Hyperspectral Image Super-Resolution,’’ submitted to IEEE TRANSACTIONS ON MEDICAL IMAGING
JIANet: Jigsaw-Invariant Self-supervised Learning of Auto-encoder Based Reconstruction for Melanoma Segmentation
A standard style for README files
A Simple and easy to use way to Visualise Embeddings!
Implementation of different kinds of Unet Models for Image Segmentation - Unet , RCNN-Unet, Attention Unet, RCNN-Attention Unet, Nested Unet
pytorch implementation for "Variational Autoencoder with Implicit Optimal Priors".
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.