ysdss's repositories
AdderNet
Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
Coursera-ML-AndrewNg-Notes
吴恩达老师的机器学习课程个人笔记
CrossStagePartialNetworks
Cross Stage Partial Networks
Deep-Learning-Approach-for-Surface-Defect-Detection
A Tensorflow implementation of "Segmentation-Based Deep-Learning Approach for Surface-Defect Detection"
Dress
好耶 是女装
face-seg
Semantic segmentation for hair, face and background
hyperspectral-autoencoders
Tools for training and using unsupervised autoencoders and supervised deep learning classifiers for hyperspectral data.
lambda-networks
Implementation of LambdaNetworks, a new approach to image recognition that reaches SOTA with less compute
learnopencv
Learn OpenCV : C++ and Python Examples
Machine-Learning-for-OpenCV-Second-Edition
Machine Learning for OpenCV Second Edition, published by Packt
Magnetic-tile-defect-datasets
dataset of the upcoming paper "Saliency of magnetic tile surface defects"
maskscoring_rcnn
Codes for paper "Mask Scoring R-CNN".
MRI-U-net
基于U-net和MRI图像的膀胱壁边缘以及膀胱肿瘤检测
MSHNet
Multi-similarity based Hyperrelation Network for Few-Shot Segmentation
pandoc
Universal markup converter
pumpkin-book
《机器学习》（西瓜书）公式推导解析，在线阅读地址：https://datawhalechina.github.io/pumpkin-book
pytorch_classification
利用pytorch实现图像分类的一个完整的代码，训练，预测，TTA，模型融合，模型部署，cnn提取特征，svm或者随机森林等进行分类，模型蒸馏，一个完整的代码
Res2Net-PretrainedModels
(ImageNet pretrained models) The official pytorch implemention of the TPAMI paper "Res2Net: A New Multi-scale Backbone Architecture"
ResNeXt.pytorch
Reproduces ResNet-V3 with pytorch
Segmentation_with_my_dataset
using u-net train my own dataset in Pytorch
surface-defect-detection
缺陷检测文献记录
triplet-attention
Official PyTorch Implementation for "Rotate to Attend: Convolutional Triplet Attention Module." [WACV 2021]
u-net-brain-tumor
U-Net Brain Tumor Segmentation
v199
Proceedings of CoLLA 2022
Visual-Classifier-Baselines
Traditional machine learning baselines for image classification
yushaodong.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes