00900nam a22001937a 4500 0 0 0 1 RIU RIU 2023-09-09 Riphah International University 0 005.1 AYM 102039 2023-09-09 00:00:00 1 2023-09-09 TH 53248 53248 Riphah International University 005.1 AYM Ayman Hassan (29210) Real-time automated defect detection of metallic conduits through borescope imaging Islamabad (unpublished) 2023 xvii, 84 p. : ill., Col. ; 30 cm. +CD Submitted in the partial fulfillment of the requirements for the degree of Master of science in software engineering in the Faculty of Computing. Includes bibliographical references Thesis supervisor: Ms. Hajra Murtaza Thesis co-supervisor: Dr. Ghulam Murtaza Thesis (MS)--Riphah International University, 2023 English Software Engineering Metallic surface Detection algorithms Deep learning Metrics FC TH