Classification of clay bricks using vision-based machine learning algorithms

Key Points

• Classification accuracy reached over 90% using advanced machine learning techniques, indicating strong performance.
• Key evidence shows that image processing and feature extraction enhance the classification effectiveness.
• Analysis focused on clay brick images with various machine learning models implemented for comparison.
• Implications could lead to more efficient manufacturing processes and quality control in the brick industry.