Deep learning for defect detection

• Main Author: Ho, Juliet Li Chew
• Other Authors: Qian Kemao
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Computer and Information Science
• Online Access: https://hdl.handle.net/10356/175998
• Institution: Nanyang Technological University

With the advancement in technology and growing interest in Artificial Intelligence (AI) related works, there has been increasing reliance on AI to improve the quality and convenience of many monotonous jobs. In the manufacturing and production industry, there is a need to improve operational efficiency and product quality for consumers. Proper packaging is essential to protect products from damage and assure the quality of products that are delivered to customers. Deep learning is often used for defect detection through image analysis and pattern recognition. Deep learning models such as convolutional neural networks (CNN) are used to learn features from data such as images to detect and classify new images.