arXiv:1608.05001
An image compression and encryption scheme based on deep learning
원문 초록
Stacked Auto-Encoder (SAE) is a kind of deep learning algorithm for unsupervised learning. Which has multi layers that project the vector representation of input data into a lower vector space. These projection vectors are dense representations of the input data. As a result, SAE can be used for image compression. Using chaotic logistic map, the compression ones can further be encrypted. In this study, an application of image compression and encryption is suggested using SAE and chaotic logistic map. Experiments show that this application is feasible and effective. It can be used for image transmission and image protection on internet simultaneously.
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Perception-Oriented Latent Coding for High-Performance Compressed Domain Semantic Inference
NIC-RobustBench: A Comprehensive Open-Source Toolkit for Neural Image Compression and Robustness Analysis
DiffO: Single-step Diffusion for Image Compression at Ultra-Low Bitrates
ABC: Adaptive BayesNet Structure Learning for Computational Scalable Multi-task Image Compression
Flexible Mixed Precision Quantization for Learned Image Compression
Structured Pruning and Quantization for Learned Image Compression
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