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.

מידע ביבליוגרפי
Main Authors: Siddiki Shan, Md. Abdul Kahhar, Quaiyum, Md. Abdul, Saha, Sugata, Nayer Anik, S. M. Navin
מחברים אחרים: Rabiul Alam, Dr. Md. Golam
פורמט: Thesis
שפה:English
יצא לאור: Brac University 2023
נושאים:
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
גישה מקוונת:http://hdl.handle.net/10361/19232

אינטרנט

http://hdl.handle.net/10361/19232

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