Semi Supervised Learning for Medical Image Segmentation, a collection of literature reviews and code implementations.

[MICCAI 2023] DAE-Former: Dual Attention-guided Efficient Transformer for Medical Image Segmentation

DA-TransUNet: Combining Dual Attention of Position and Channel with Transformer U-net for Medical Image Segmentation

这是一个YoloV4-tiny-pytorch的源码，可以用于训练自己的模型。

😄博客论文列表：分系列整理

Towards Reliable Medical Image Segmentation by utilizing Evidential Calibrated Uncertainty

Comprehensive PyTorch Library for deep learning uncertainty quantification techniques.

This repository contains a collection of surveys, datasets, papers, and codes, for predictive uncertainty estimation in deep learning models.

A collection of loss functions for medical image segmentation

Research on Multi-temporal Cloud Removal Using D-S Evidence Theory and Cloud Segmentation Model

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

计算机自学指南

HRSID: high resolution sar images dataset for ship detection, semantic segmentation, and instance segmentation tasks.

GroupMixAttention and GroupMixFormer

Ship image segmentation

We constructed a marine ship semantic segmentation dataset named SeaShipsSeg, which consists of 1200 manually finely labeled ship images of 6 principal ship types, including bulk cargo carrier, con…

Pipeline for training UNet using Keras for the problem of ships segmentation

LFG-Net for Precise Ship Instance Segmentation in SAR Images

This repository includes the code of Computer Vision, such as Object Detection, Semantic segmentation，Pedestrian re-identification and so on.The code is implemented in Tensorflow2.0+ and Pytorch.If…

This repository provides a comprehensive list of radar and optical satellite datasets curated for ship detection, classification, semantic segmentation, and instance segmentation tasks. These datas…

This is the available code for the paper `evidential fully convolutional network for semantic segmentation (arXiv preprint arXiv:2103.13544)

Code for paper "Evidence fusion with contextual discounting for multi-modality medical image segmentation"

Code for paper "Lymphoma segmentation from 3D PET-CT images using a deep evidential network"

Trustworthy AI method based on Dempster-Shafer theory - application to fetal brain 3D T2w MRI segmentation

Language Understanding Evaluation benchmark for Chinese: datasets, baselines, pre-trained models,corpus and leaderboard

A Python library for performing calculations in the Dempster-Shafer theory of evidence.