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.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριοι συγγραφείς: Siddiki Shan, Md. Abdul Kahhar, Quaiyum, Md. Abdul, Saha, Sugata, Nayer Anik, S. M. Navin
Άλλοι συγγραφείς: Rabiul Alam, Dr. Md. Golam
Μορφή: Thesis
Γλώσσα:English
Έκδοση: Brac University 2023
Θέματα:
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
Διαθέσιμο Online:http://hdl.handle.net/10361/19232

Διαδίκτυο

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

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