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Abstract:  AI-driven defect detection   uses artificial intelligence and machine learning to automate and enhance quality control in manufacturing . These systems use high-resolution cameras and sensors with advanced computer vision algorithms to rapidly and accurately identify flaws that may be difficult for humans to spot.   Keywords: AI in Manufacturing, Computer Vision, Defect Detection, Deep Learning, Automation, Quality Control, Industrial AI Let's explore the AI-driven defect detection in details  Introduction In modern manufacturing, maintaining high product quality while minimizing production costs is essential for competitiveness. Traditional quality inspection methods, heavily reliant on human expertise, often face challenges such as fatigue, inconsistency, and limited scalability. With the rise of Artificial Intelligence (AI) and computer vision , the manufacturing industry has entered a new era of AI-driven defect detection —a transformativ...

Abstract Deep learning (DL), a branch of machine learning (ML) and artificial intelligence (AI) is nowadays considered as a core technology of today’s Fourth Industrial Revolution (4IR or Industry 4.0). Deep learning neural networks  produce excellent results in various pattern recognition tasks . It is of great practical importance to answer some open questions regarding model design and parameterization, and to understand how input data are converted into meaningful knowledge at the output. Due to its learning capabilities from data, DL technology originated from artificial neural network (ANN), has become a hot topic in the context of computing, and is widely applied in various application areas like healthcare, visual recognition, text analytics, cybersecurity, and many more. However, building an appropriate DL model is a  challenging  task, due to the dynamic nature and variations in real-world problems and data. Moreover, the lack of core understand...