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adversarial-robustness-toolbox

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams

annotated_deep_learning_paper_implementations

🧑‍🏫 50! Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

cbam.pytorch

Non-official implement of Paper：CBAM: Convolutional Block Attention Module

deep-learning-for-image-processing

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

fcanet

FcaNet: Frequency Channel Attention Networks

gradcam-of-pmg

This is an implementation of PMG, and I visualize the features abstracted by convs. It's helpful for me to understand the structure of PMG.

lhy_machine_learning

李宏毅2021春季机器学习课程课件及作业

machine-learning-course

:speech_balloon: Machine Learning Course with Python:

netron

Visualizer for neural network, deep learning, and machine learning models

paddlehub

Awesome pre-trained models toolkit based on PaddlePaddle. (400+ models including Image, Text, Audio, Video and Cross-Modal with Easy Inference & Serving)

pca-net

Progressive Co-Attention Network for Fine-Grained Visual Classification

pmg-progressive-multi-granularity-training

Code release for Fine-Grained Visual Classification via Progressive Multi-Granularity Training of Jigsaw Patches (ECCV2020)

u-2-net

The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."

ws-dan.pytorch

A PyTorch implementation of WS-DAN (Weakly Supervised Data Augmentation Network) for FGVC (Fine-Grained Visual Classification)

ws_dan_pytorch

PyTorch Implementation Of WS-DAN(See Better Before Looking Closer: Weakly Supervised Data Augmentation Network for Fine-Grained Visual Classification)

yolov3_adversarial_defense