Popular GitHub Repositories for Mi Fgsm

Advbox is a toolbox to generate adversarial examples that fool neural networks in PaddlePaddle、PyTorch、Caffe2、MxNet、Keras、TensorFlow and Advbox can benchmark the robustness of machine learning models. Advbox give a command line tool to generate adversarial examples with Zero-Coding.

A Python library for adversarial machine learning focusing on benchmarking adversarial robustness.

《照片修复小小助手》是一款基于微信AI能力的微信小程序，实现了图片选定区域的消除修复功能，纯客户端实现，无服务端。Inpaint_wechat is a WeChat mini-program based on the WeChat AI capabilities, implementing the functionality of inpainting and repairing selected areas in images, which is purely implemented by the client and has no server.

Implementation of Papers on Adversarial Examples

CTNet: A Convolutional Transformer Network for EEG-Based Motor Imagery Classification

Simple pytorch implementation of FGSM and I-FGSM

Tensorflow Implementation of Adversarial Attack to Capsule Networks

A new approach based on a 10-layer one-dimensional convolution neural network (1D-CNN) to classify five brain states (four MI classes plus a 'baseline' class) using a data augmentation algorithm and a limited number of EEG channels. Paper: https://doi.org/10.1088/1741-2552/ac4430

PyTorch library for adversarial attack and training

This repository contains the implementation of three adversarial example attack methods FGSM, IFGSM, MI-FGSM and one Distillation as defense against all attacks using MNIST dataset.

A curated collection of resources focused on the Mechanistic Interpretability (MI) of Large Multimodal Models (LMMs). This repository aggregates surveys, blog posts, and research papers that explore how LMMs represent, transform, and align multimodal information internally.

AMD OpenVX modules: such as, neural network inference, 360 video stitching, etc.

Implementation of gradient-based adversarial attack(FGSM,MI-FGSM,PGD)

The ChatGPT/DeepSeek Voice Assistant uses a Raspberry Pi (or desktop) to enable spoken conversation with OpenAI or DeepSeek large language models. This implementation listens to speech, processes the conversation through the OpenAI/DeepSeek service, and responds back. Like Apple Siri, Amazon Alex, Google Nest Home, Mi XiaoAi etc.

SHIELD: Fast, Practical Defense and Vaccination for Deep Learning using JPEG Compression

A research repository of deep learning on electroencephalographic (EEG) for Motor imagery(MI), including eeg data processing(visualization & analysis), papers(research and summary), deep learning models(reproduction and experiments).

The first real-world adversarial attack on MTCNN face detetction system to date

[ACM MobiCom 2022] "PyramidFL: Fine-grained Data and System Heterogeneity-aware Client Selection for Efficient Federated Learning" by Chenning Li, Xiao Zeng, Mi Zhang, and Zhichao Cao.

[NeurIPS 2022] "FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction" by Samiul Alam, Luyang Liu, Ming Yan, and Mi Zhang

[NeurIPS 2020] "Does Unsupervised Architecture Representation Learning Help Neural Architecture Search?" by Shen Yan, Yu Zheng, Wei Ao, Xiao Zeng, Mi Zhang