yahaha (yjx123456jason)

yjx123456jason

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mmdetection

OpenMMLab Detection Toolbox and Benchmark

License:Apache-2.0Stargazers:0Issues:0Issues:0

pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

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annotated_deep_learning_paper_implementations

🧑‍🏫 59 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, ... 🧠

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Sherlock

This repository contains experiments for different publications at the intersection of Computer Vision and Computer Security.

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CLIP

Contrastive Language-Image Pretraining

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AMT-GAN

The official implementation of our CVPR 2022 paper "Protecting Facial Privacy: Generating Adversarial Identity Masks via Style-robust Makeup Transfer".

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malware_detection

结合cuckoo沙箱调用及报告处理实现基于API调用序列和网络流量的恶意代码检测

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moco

PyTorch implementation of MoCo: https://arxiv.org/abs/1911.05722

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Malware-Detection-Using-Deep-Learning-1

Malware Detection with help of Image processing

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Malware-Detection-using-Deep-Learning

Firstly, we generate images from benign and malware executable files. Secondly, by using deep learning, we train a model to detect malware files. Then, by the trained model, we try to classify a file as malware or not. By using malware images and deep learning, we can detect malware fast since we do not need any static analysis or dynamic analysis.

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Malware_Detection_Using_Deep_Learning

An approach to detect Malware Files using Deep Learning

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malware-detection-based-on-cnn

基于卷积神经网络的恶意软件检测方法

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