Abstract: Image watermarking techniques have continuously evolved to address new challenges and incorporate advanced features. The advent of data-driven approaches has enabled the processing and ...
Abstract: The existing body of research on quantum embedding techniques is not only confined in scope but also lacks a comprehensive understanding of the intricacies of the quantum embedding process.
This project implements a Variational Autoencoder (VAE) for image generation. Unlike standard autoencoders, VAE learns a probabilistic latent space by encoding images to a distribution and sampling ...
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