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But what actually  happens is, We feed the generator of GAN1 with the non IID noise vector of size 256 \u00d7 512 i.e. 256 noise vector of size 512. All other generators use the training images with different sizes. With this, GAN1 generates R, G, B images each of size 8 \u00d7 8 \u00d7 3. Similarly, GAN2, GAN3, GAN4 and GAN5 generate images of, 16 \u00d7 16 \u00d7 3, 32 \u00d7 32\u00d7 3, 64 \u00d7 64 \u00d7 3 and 128 \u00d7 128 \u00d7 3, respectively.","order":5,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 July 2025","order":6,"name":"change_date","label":"Change Date","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"Correction","order":7,"name":"change_type","label":"Change Type","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"A Correction to this paper has been published:","order":8,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"https:\/\/doi.org\/10.1007\/s11227-025-07703-y","URL":"https:\/\/doi.org\/10.1007\/s11227-025-07703-y","order":9,"name":"change_details","label":"Change Details","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"1008"}}