flower96's Stars
jionie/imgclsmob
Sandbox for training convolutional networks for computer vision
albumentations-team/albumentations
Fast and flexible image augmentation library. Paper about the library: https://www.mdpi.com/2078-2489/11/2/125
taki0112/BigGAN-Tensorflow
Simple Tensorflow implementation of "Large Scale GAN Training for High Fidelity Natural Image Synthesis" (BigGAN)
fengdu78/Data-Science-Notes
数据科学的笔记以及资料搜集
qd301/FocusRectificationLogisticRegression
Single-Label Multi-Class Image Classification by Deep Logistic Regression
jacobgil/pytorch-grad-cam
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
zhoubolei/CAM
Class Activation Mapping
utkuozbulak/pytorch-cnn-visualizations
Pytorch implementation of convolutional neural network visualization techniques
TheAlgorithms/Python
All Algorithms implemented in Python
lessw2020/Ranger-Deep-Learning-Optimizer
Ranger - a synergistic optimizer using RAdam (Rectified Adam), Gradient Centralization and LookAhead in one codebase
LiyuanLucasLiu/RAdam
On the Variance of the Adaptive Learning Rate and Beyond
wjn922/Optimizer-Experiments-Pytorch
SGD/ADAM/Amsgrad/AdamW/RAdam/Lookahead
libuyu/mmdetection
Open MMLab Detection Toolbox with PyTorch
xyfZzz/GHM_Loss_Tensorflow
tensorflow implementation of GHM-C Loss
vinta/awesome-python
An opinionated list of awesome Python frameworks, libraries, software and resources.
weiaicunzai/awesome-image-classification
A curated list of deep learning image classification papers and codes
yunjey/pytorch-tutorial
PyTorch Tutorial for Deep Learning Researchers
QLMX/data_mining_models
Basic data mining model, including feature importance display
xinario/awesome-gan-for-medical-imaging
Awesome GAN for Medical Imaging
hindupuravinash/the-gan-zoo
A list of all named GANs!
bnu-wangxun/Deep_Metric
Deep Metric Learning
L1aoXingyu/pytorch-beginner
pytorch tutorial for beginners
justmarkham/scikit-learn-videos
Jupyter notebooks from the scikit-learn video series