Optimal transport theory based GAN for medical image augmentation and classification

Optimal transport theory based GAN for medical image augmentation and classification

This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.

Opis bibliograficzny
Główni autorzy:	Siddiki Shan, Md. Abdul Kahhar, Quaiyum, Md. Abdul, Saha, Sugata, Nayer Anik, S. M. Navin
Kolejni autorzy:	Rabiul Alam, Dr. Md. Golam
Format:	Praca dyplomowa
Język:	English
Wydane:	Brac University 2023
Hasła przedmiotowe:	Optimal Transport(OT) Theory Generative Adversarial Networks (GANs) Unsupervised neural networks Wasserstein distance Maximum Mean Discrepancy(MMD) Chest X-Ray Covid-19 Viral pneumonia Lung opacity Natural language processing (Computer science) Machine learning
Dostęp online:	http://hdl.handle.net/10361/19232

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