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Αυτο-εποπτευόμενο GAN×Γενετικό Ανταγωνιστικό Δίκτυο×
ΠεδίοΒαθιά ΜάθησηΒαθιά Μάθηση
ΟικογένειαMachine learningMachine learning
Έτος προέλευσης20192014
ΔημιουργόςChen, T., Zhai, X., Ritter, M., Lucic, M., & Houlsby, N.Goodfellow, I. et al.
ΤύποςGenerative model with self-supervised auxiliary tasksGenerative deep learning (adversarial two-network game)
Θεμελιώδης πηγήChen, T., Zhai, X., Ritter, M., Lucic, M., & Houlsby, N. (2019). Self-Supervised GANs via Auxiliary Rotation Loss. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 12154–12163. link ↗Goodfellow, I. et al. (2014). Generative Adversarial Nets. NeurIPS. link ↗
Εναλλακτικές ονομασίεςSS-GAN, Self-supervised GAN, Self-supervised Generative Adversarial Network, GAN with self-supervised auxiliary tasksÜretici Çekişmeli Ağ (GAN), GAN, generative adversarial nets, adversarial network
Συναφείς54
ΣύνοψηSelf-supervised GAN augments a standard Generative Adversarial Network with one or more self-supervised auxiliary tasks — such as predicting image rotation or patch position — that stabilise adversarial training and yield a discriminator that learns rich, transferable representations from unlabeled data without requiring manual annotations.A Generative Adversarial Network (GAN), introduced by Ian Goodfellow and colleagues in 2014, produces realistic synthetic data through the competition of two neural networks — a generator and a discriminator. It is widely used for image synthesis, data augmentation, and distribution estimation.
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ScholarGateΣύγκριση μεθόδων: Self-supervised GAN · Generative Adversarial Network. Ανακτήθηκε στις 2026-06-17 από https://scholargate.app/el/compare