rsdljm Goto Github PK

localvit

lstm_multi_modal_unet

Implementation of ICIVC 2019 paper "LSTM multi-modal UNet for Brain Tumor Segmentation"

medical-transformer

Official Pytorch Code for "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" - MICCAI 2021

medical_image_segmentation

Medical image segmentation ( Eye vessel segmentation)

mfpnet

PyTorch implementation for "Remote Sensing Change Detection Based on Multidirectional Adaptive Feature Fusion and Perceptual Similarity"

miccai-opensourcepapers

MICCAI 2020 Open Source Papers

mmsegmentation

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

mnist-svhn-transfer

PyTorch Implementation of CycleGAN and SSGAN for Domain Transfer (Minimal)

models

Models and examples built with TensorFlow

models-pytorch

This is a torchvision style CNN models collection based on pytorch.

monocular-depth-prediction-with-residual-denseaspp-network

Monocular depth estimation is an ill-posed problem because infinite 3D scenes can be projected to the same 2D scenes. Most recent methods focus on image-level information from deep convolutional neural networks, while training them may suffer from slow convergence and accuracy degeneration, especially for deeper network and more feature channels. Based on an encoder-decoder framework, we propose a novel Residual DenseASPP Network. In our Residual DenseASPP network, we define features as low/mid/high vision features, and use two-kinds of skip connection to learn useful features with certain layers, where feature concentration in dense block is used to generate more features in the same layer, and feature summation in residual block is used to increase backward gradient. The experimental results show that high vision features require more channels by feature concentration, while low/mid vision features need better convergence by feature summation. Experiments show that our proposed approach achieves state-of-the-art performance on both NYUv2 and Make3D datasets.

mspsnet-change-detection-tgrs

The Pytorch implementation for Deep Multiscale Siamese Network with Parallel Convolutional Structure and Self-Attention for Change Detection (MSPSNet)

multi-scale-attention

Code for our paper "Multi-scale Guided Attention for Medical Image Segmentation"

multimodal-remote-sensing-toolkit

A python tool to perform deep learning experiments on multimodal remote sensing data.

multiresunet

multiresunet-1

MultiResUNet implementation in PyTorch; MultiResUNet: Rethinking the U-Net Architecture for Multimodal

nlp_ability

总结梳理自然语言处理工程师(NLP)需要积累的各方面知识，包括面试题，各种基础知识，工程能力等等，提升核心竞争力

non-local-u-nets-2d-block

Inplement 2D global aggregation block of Non-local-U-Nets. Written in pytorch.

nrt-monitor

nuclei-detecion-using-u-net-family

This repository is a implementation of UNet ,Wide-UNet and UNet++ with keras and tensorflow using python.

opencvtutorials

OpenCV-Python4.1 中文文档

paper-reading-note

和李沐一起读论文

pdrscd

基于『飞桨』的遥感变化检测工具（Remote sensing change detection tool based on『PaddlePaddle』）

pix2pix-tensorflow

Tensorflow port of Image-to-Image Translation with Conditional Adversarial Nets https://phillipi.github.io/pix2pix/

prcv2021-change-detection-contest-2nd-place-solution

Remote sensing building change detection

prcv2021_changedetection_top3

PRCV2021变化检测竞赛第三名解决方案

pyramid-attention-networks-pytorch

Implementation of Pyramid Attention Networks for Semantic Segmentation.

pytorch-cyclegan-and-pix2pix

Image-to-Image Translation in PyTorch

pytorch-grad-cam

Many Class Activation Map methods implemented in Pytorch for CNNs and Vision Transformers. Including Grad-CAM, Grad-CAM++, Score-CAM, Ablation-CAM and XGrad-CAM

pytorch-image-models

PyTorch image models, scripts, pretrained weights -- (SE)ResNet/ResNeXT, DPN, EfficientNet, MixNet, MobileNet-V3/V2, MNASNet, Single-Path NAS, FBNet, and more