Tu.P10.A-50
Extreme Parameter Efficiency in Quantum Machine Learning for Cervical Cancer Classification
MD Majedul Islam, Kazi Fahim Ahmad Nasif, Nobel Dhar, Mahmut Karakaya, Selena He, Kennesaw State University
Session:
Tu.P10: Foundation Models, Federated & Trustworthy AI Poster
Track:
Biomedical Imaging and Image Processing
Location:
Hall E; Bay A, Board #50
Presentation Time:
Tuesday, 28 July, 16:30 - 18:30
Presentation
Discussion
Resources
No resources available.
Session Tu.P10
Tu.P10.A-46: TAYLORKAN-VIT: PARAMETER-EFFICIENT VISION TRANSFORMERS FOR MEDICAL IMAGE CLASSIFICATION
Kaniz Fatema, Emad Mohammed, Sukhjit Singh Sehra, Wilfrid Laurier University
Tu.P10.A-47: GEOVIG: GEOMETRY-AWARE GRAPH REASONING FOR MOBILE VISION TASKS IN NATURAL AND MEDICAL IMAGES
Omar Alsaqa, Emad Mohammed, Saiqa Aleem, Wilfrid Laurier University
Tu.P10.A-48: PnPD: Plug-and-Play Dual-Path Framework for Computer-Aided Detection with Decoupled Localization and Subtype Classification
Yung-Han Chen, National Yang Ming Chiao Tung University; Jian-Yu Jiang-Lin, National Taiwan University; Tsung-Hsing Chen, Chang Gung Memorial Hospital; Chang-Fu Kuo, School of Medicine, Chang Gung University; Hung-Yu Wu, Daikso; Wen-Huang Cheng, National Taiwan University; Juinn-Dar Huang, National Yang Ming Chiao Tung University
Tu.P10.A-49: PIXEL-LEVEL DATA AUGMENTATION FOR ROBUST MEDICAL IMAGE CLASSIFICATION
Meng Xu, Bin Hu, Boyang Li, Kuan Huang, Kean University
Tu.P10.A-50: Extreme Parameter Efficiency in Quantum Machine Learning for Cervical Cancer Classification
MD Majedul Islam, Kazi Fahim Ahmad Nasif, Nobel Dhar, Mahmut Karakaya, Selena He, Kennesaw State University
Resources
No resources available.