Ayman Hassan (29210) <br/><br/>
Real-time automated defect detection of metallic conduits through borescope imaging  

 - Islamabad   (unpublished)  2023 
 - xvii, 84 p.  : ill., Col.  ; 30 cm.  +CD  
<br/><br/> 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<br/>Thesis co-supervisor: Dr. Ghulam Murtaza 
<br/><br/>Thesis (MS)--Riphah International University, 2023 
<br/><br/><br/>English 
<br/><br/><label>Subjects--Topical Terms: </label><br/>Software Engineering--Metallic surface--Detection algorithms--Deep learning--Metrics--FC
<br/><br/><label>Dewey Class. No.: </label>005.1  / AYM