PyTorch implementation for "WDM: 3D Wavelet Diffusion Models for High-Resolution Medical Image Synthesis" (DGM4MICCAI 2024)

PyTorch 3D U-Net implementation for Multimodal Brain Tumor Segmentation (BraTS 2021)

中英文敏感词、语言检测、中外手机/电话归属地/运营商查询、名字推断性别、手机号抽取、身份证抽取、邮箱抽取、中日文人名库、中文缩写库、拆字词典、词汇情感值、停用词、反动词表、暴恐词表、繁简体转换、英文模拟中文发音、汪峰歌词生成器、职业名称词库、同义词库、反义词库、否定词库、汽车品牌词库、汽车零件词库、连续英文切割、各种中文词向量、公司名字大全、古诗词库、IT词库、财经词库、成语词库、地名词库、…

This is the FER+ new label annotations for the Emotion FER dataset.

A deep neural net toolkit for emotion analysis via Facial Expression Recognition (FER)

A landmark-driven method on Facial Expression Recognition (FER)

A CNN based pytorch implementation on facial expression recognition (FER2013 and CK+), achieving 73.112% (state-of-the-art) in FER2013 and 94.64% in CK+ dataset

[CVPR 2025] SuperLightNet: Lightweight Parameter Aggregation Network for Multimodal Brain Tumor Segmentation

[IEEE TMI] DiffMIC-v2: Medical Image Classification via Improved Diffusion Network

LHU-Net: A Lean Hybrid U-Net for Cost-efficient, High-performance Volumetric Medical Image Segmentation

Code for the paper Detecting Heart Disease from Multi-View Ultrasound Images via Supervised Attention Multiple Instance Learning

Implementation of the paper “An Efficient CNN Model for COVID-19 Disease Detection Based on X-Ray Image Classification.” Reproduces the proposed architecture and evaluation for automated COVID-19 d…

The PyTorch re-implement of a branch-aware coronary centerline extraction in CT Angiography images. (paper: 'Branch-Aware Double DQN for Centerline Extraction in Coronary CT Angiography')

Comparative study of Barlow Twins self-supervised pre-training vs. ImageNet fine-tuning for medical image analysis across CT and histology domains

Medical imaging diagnosis assistant that can detect diseases from X-rays, MRIs, and CT scans with expert-level accuracy - healthcare-focused computer vision.

Biomedisa is a free and open-source application for segmenting 3D images such as CT and MRI scans, developed at The Australian National University CTLab.

MOOSE (Multi-organ objective segmentation) a data-centric AI solution that generates multilabel organ segmentations to facilitate systemic TB whole-person research.The pipeline is based on nn-UNet …

This repository contains a paper collection of the methods for document image processing, including appearance enhancement, deshadowing, dewarping, deblurring, binarization and so on.

Fast Image Processing with Fully-Convolutional Networks

This project contains some interesting image processing algorithms that were wrote in python and c++ from scratch.

Image processing in Python

deep learning for image processing including classification and object-detection etc.

AI-assisted Deciphering Oracle Bone Script

code for Image Manipulation Detection by Multi-View Multi-Scale Supervision

Official repository for "OTMorph: Unsupervised Multi-domain Abdominal Medical Image Registration Using Neural Optimal Transport".

《深度学习入门：基于Python的理论与实现》电子版及配套代码​。​

Exploring large language models for knowledge graph completion. ICASSP 2025