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Machine learningDeep learning / NLP / CV

Mtandao Jenereta Ushindani Ulioboreshwa (Fine-Tuned Generative Adversarial Network)

Mtandao Jenereta Ushindani Ulioboreshwa (Fine-Tuned GAN) huanza kutoka kwa mtandao jenereta ushindani mkubwa uliofunzwa awali na kuendelea na mafunzo ya ushindani kwenye seti ndogo ya data lengwa, kuruhusu modeli kuunda sampuli za ubora wa juu katika kikoa kipya bila kuhitaji kufunzwa kuanzia mwanzo. Mbinu hii ya uhamishaji hupunguza kwa kiasi kikubwa mahitaji ya data na kompyuta huku ikihifadhi uwakilishi tajiri wa vipengele uliojifunzwa wakati wa mafunzo ya awali.

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Vyanzo

  1. Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., Courville, A., & Bengio, Y. (2014). Generative Adversarial Nets. Advances in Neural Information Processing Systems (NeurIPS), 27. link
  2. Mo, S., Cho, M., & Shin, J. (2020). Freeze the Discriminator: a Simple Baseline for Fine-Tuning GANs. CVPR 2020 Workshop on AI for Content Creation. link

Jinsi ya kunukuu ukurasa huu

ScholarGate. (2026, June 3). Fine-Tuned Generative Adversarial Network (Domain-Adaptive GAN via Transfer). ScholarGate. https://scholargate.app/sw/deep-learning/fine-tuned-generative-adversarial-network

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ScholarGateFine-Tuned Generative Adversarial Network (Fine-Tuned Generative Adversarial Network (Domain-Adaptive GAN via Transfer)). Imepatikana 2026-06-15 kutoka https://scholargate.app/sw/deep-learning/fine-tuned-generative-adversarial-network · Seti ya data: https://doi.org/10.5281/zenodo.20539026