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A Comprehensive Survey of Transformers for Computer Vision
Our next step is to review the state-of-the-art in each category and list the available models.
Learning-Driven Lossy Image Compression; A Comprehensive Survey
This paper aims to survey recent techniques utilizing mostly lossy image compression using ML architectures including different auto-encoders (AEs) such as convolutional auto-encoders (CAEs), variational auto-encoders (VAEs), and AEs with hyper-prior models, recurrent neural networks (RNNs), CNNs, generative adversarial networks (GANs), principal component analysis (PCA) and fuzzy means clustering.
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