विधियों की तुलना करें

	अर्ध-पर्यवेक्षित GAN	जनरेटिव एडवरसैरियल नेटवर्क
क्षेत्र	गहन अधिगम	गहन अधिगम
परिवार	Machine learning	Machine learning
उद्भव वर्ष	2016	2014
प्रवर्तक	Odena, A.; Salimans, T. et al.	Goodfellow, I. et al.
प्रकार	Semi-supervised generative model	Generative deep learning (adversarial two-network game)
मौलिक स्रोत	Salimans, T., Goodfellow, I., Zaremba, W., Cheung, V., Radford, A., & Chen, X. (2016). Improved Techniques for Training GANs. Advances in Neural Information Processing Systems (NeurIPS), 29.	Goodfellow, I. et al. (2014). Generative Adversarial Nets. NeurIPS.
उपनाम	SGAN, Semi-GAN, semi-supervised generative adversarial network, GAN-based semi-supervised learning	Üretici Çekişmeli Ağ (GAN), GAN, generative adversarial nets, adversarial network
संबंधित	5	4
सारांश	Semi-supervised GAN (SGAN) extends the standard GAN discriminator to simultaneously classify labeled examples into K real classes and detect generated fakes as a (K+1)-th class, letting the generator's synthetic data act as implicit regularization and allowing strong classifiers to be trained with very few labeled examples.	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.