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Titlebook: Computer Vision and Image Processing; 7th International Co Deep Gupta,Kishor Bhurchandi,Sanjeev Kumar Conference proceedings 2023 The Edito

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Advances in Cryptology – ASIACRYPT 2023 than classification architectures and require roughly twice as many network parameters. This large number of network layers may result in vanishing gradient or redundant computation, increased computational complexity and more memory consumption. Therefore, it is essential to develop an efficient d
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Exact Security Analysis of ASCON an embedder network (to hide a message inside the container) and an extractor network(to extract the hidden message from the encoded image). In the proposed method, we employ the generative power of a variational autoencoder with adversarial training to embed images. At the extractor, a vanilla con
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https://doi.org/10.1007/978-3-662-53018-4xplore the application of data hiding to analyse the model’s performance. Share-GAN consists of an embedder network (to encode secret messages into a cover), a U-Net autoencoder (that consists of encoder and decoder). The embedder’s encoder network is custom trained to act as an extractor network (t
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