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.

Detaylı Bibliyografya
Asıl Yazarlar:	Siddiki Shan, Md. Abdul Kahhar, Quaiyum, Md. Abdul, Saha, Sugata, Nayer Anik, S. M. Navin
Diğer Yazarlar:	Rabiul Alam, Dr. Md. Golam
Materyal Türü:	Tez
Dil:	English
Baskı/Yayın Bilgisi:	Brac University 2023
Konular:	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
Online Erişim:	http://hdl.handle.net/10361/19232

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