Research from CPE KMUTT explores the retention of cultural knowledge in AI training using synthetic data and has been accepted for presentation at WiML 2026.
CPE KMUTT researchers developed RenalRQKV-Net, an AI framework for kidney CT image classification that achieved 99.63% accuracy and won the Best Paper Award at EECSI 2026 in Indonesia.
Research from CPE KMUTT introduces a secure authentication system that verifies both users and hospital websites to help prevent website spoofing. With a processing time of just 1.49 milliseconds, the system has potential for resource-constrained medical devices. The research was published in SN Computer Science.