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深度学习 隐写术;使用神经网络以图藏图(NIPS2017),torch版本 paper:Hiding Images in Plain Sight:Deep Steganography https://papers.nips.cc/paper/2017/hash/838e8afb1ca34354ac209f53d90c3a43-Abstract.html
Pytorch implementation of paper "HiDDeN: Hiding Data With Deep Networks" by Jiren Zhu, Russell Kaplan, Justin Johnson, and Li Fei-Fei
The source code of paper "An Embedding Cost Learning Framework Using GAN"
Fully Convolutional DenseNets for semantic segmentation.
Unofficial implementations of some classical CNN backbones with pytorch
The basic distribution probability Tutorial for Deep Learning Researchers
A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
(ImageNet pretrained models) The official pytorch implemention of the TPAMI paper "Res2Net: A New Multi-scale Backbone Architecture"
Steganography via adversarial training
Official code for UDH: Universal Deep Hiding for Steganography, Watermarking, and Light Field Messaging (Accepted at NeurIPS2020).
Implementation of "Embedding Watermarks into Deep Neural Networks," in Proc. of ICMR'17.
Official pytorch implementation of paper "Image Disentanglement Autoencoder for Steganography without Embedding" (CVPR2022).
Text steganography based on Markov chains
Steganographic text via language models
Paper implementation for "End-to-end Trained CNN Encoder-Decoder Networks for Image Steganography"
deep learning for image processing including classification and object-detection etc.
Ever sent a hidden message in invisible ink to your friends? Are you intrigued by the idea of cryptic message exchange? How about using images for this exchange? Steganography is what you need! It is one of the techniques of encryption and over the years, steganography has been used to encode a lower resolution image into a higher resolution image. But steganography using naive methods, like LSB manipulation, is susceptible to statistical analysis. Our model extends existing deep learning research for encoding multiple secret images onto a single cover by leveraging convolutional neural networks based deep learning architectures. DeepSteg allows senders to embed up to three secret images onto a single cover using an encoder network and then have multiple decoder networks to obtain the embedded secrets.
An Image Encryption Scheme Based on Chaotic Logarithmic Map and Key Generation using Deep CNN
PyTorch implementations of Generative Adversarial Networks.
RepVGG: Making VGG-style ConvNets Great Again
Models and examples built with TensorFlow
[T-IFS] RNN-SM: Fast Steganalysis of VoIP Streams Using Recurrent Neural Network
Spectrogram is selected as preprocessing feature of audio clips and a feature representation method based on deep residual network (Spec-ResNet) is proposed to detect audio steganography.
Steganalysis based deep learning
SteganoGAN is a tool for creating steganographic images using adversarial training.
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TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.