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AI upscaling leverages deep learning models, particularly Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), to predict and generate high-frequency details that are missing from low-resolution images. These models are trained on vast datasets of paired low-resolution and high-resolution images, allowing them to learn the patterns and features that distinguish high-quality images from their lower-resolution counterparts.

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Artificial Intelligence (AI) has made tremendous strides in image processing, enabling the enhancement of image quality through upscaling techniques. AI-upscaled images refer to the process of using machine learning algorithms to increase the resolution of an image beyond its original limits. This technology has numerous applications, ranging from enhancing low-resolution images for better viewing experiences to restoring damaged or deteriorated photographs. However, if this archive contains images enhanced through

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