![]() ![]() Therefore, this thesis uses the GAN to colorize images. In recent years, the Generative Adversarial Networks (GAN) have outperformed in the fields of image generation, image denoising, image style conversion, etc., which fully proves the potential of GAN in image processing. Therefore, the colorization research based on deep learning method has significance and broad application prospects. In the past, methods of image colorization were based on color transfer and expansion, requiring manual intervention, and the coloring effect was unsatisfactory. In recent years, with the development of digital media technology, many methods for coloring gray-scale images have been proposed. ![]() With the development of artificial intelligence, there is a clear trend to combine computer technology with traditional industries.
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