Titlebook: A Primer on Generative Adversarial Networks; Sanaa Kaddoura Book 2023 The Editor(s) (if applicable) and The Author(s), under exclusive lic

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純樸

Legion

https://doi.org/10.1007/978-1-4419-5675-0 networks: the generator and the discriminator are mainly made up of a deep neural network. The generator model aims to generate new data that looks like the real one. Typically, the generator model is composed of multiple up-sampling layers. The discriminator aimed to differentiate between actual d

凈禮

Etymology

978-3-031-32660-8The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

里程碑

廢墟

誘導(dǎo)

易受刺激

2191-5768 ation, deep fake, CycleGANs, and more..By the end of the book, readers will have an essential understanding of GANs and be able to write their own GAN code. They can apply this knowledge to their projects, rega978-3-031-32660-8978-3-031-32661-5Series ISSN 2191-5768 Series E-ISSN 2191-5776

泄露

Overview of GAN Structure,n this case, in particular, feminist and gender-related research—was marginalized, as were the experts in the institution who carry that knowledge. Therefore, the World Bank’s evidence-based approach led to certifying a thin version of CCTs, minus any goals for altering gender relations or outcomes.