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.

التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Siddiki Shan, Md. Abdul Kahhar, Quaiyum, Md. Abdul, Saha, Sugata, Nayer Anik, S. M. Navin
مؤلفون آخرون: Rabiul Alam, Dr. Md. Golam
التنسيق: أطروحة
اللغة:English
منشور في: Brac University 2023
الموضوعات:
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
الوصول للمادة أونلاين:http://hdl.handle.net/10361/19232

الانترنت

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

مواد مشابهة