Items where Department is "Information and Computer Science" and Year is 2026
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Number of items: 2.
SwinFSR: Landmark-Guided Multiscale Swin Transformer for Identity-Preserving Face Super Resolution. Masters thesis, King Fahd University of Petroleum and Minerals.
Explainable Deep Learning Based Viral Sequence Classification and Potential Threat Identification for Biosecurity Surveillance. Masters thesis, King Fahd University of Petroleum and Minerals.