Browsing Bilişim Sistemleri Mühendisliği / Information Systems Engineering by Subject "Deep learning"

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Automatic Detection and Classification of Defective Areas on Metal Parts by Using Adaptive Fusion of Faster R-CNN and Shape From Shading

Selamet, Feyza; Cakar, Serap; Kotan, Muhammed (2022-11-21)

Computer vision and deep learning approaches have an important role in industrial inspection systems. Computer vision technology is essential for fast, defect-free control of products in the production line. The importance ...
Dynamic Modeling With Integrated Concept Drift Detection for Predicting Real-Time Energy Consumption of Industrial Machines

Kahraman, Abdulgani; Kantardzic, Mehmet; Kotan, Muhammed (2022-09-28)

Industrial machinery is a significant energy consumer, and its CO2 emissions have increased dramatically in recent years. Therefore, energy efficiency is becoming crucial for businesses, governments, as well as the planet. ...