[This article belongs to Volume - 56, Issue - 01, 2024]
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-30-04-2024-41

Title : PERFORMANCE EVALUATION OF DEEP LEARNING BASED METHODS FOR DETECTING WOOD QUALITY DEFECTS
Dr. M. Manju

Abstract :

The wood manufacturing or wood product based industries need to check the wood quality defects to improve the quality of wood products. The traditional wood quality testing techniques has a many problems such as extravagant, low accuracy rate for wood defects and awkward routine. The traditional wood quality testing methods didn’t accurately show the correct location and wood size of internal defects. In this research, deep learning based some effective wood defect detective methods are presented with its summarized details to show which method is invoke better. The performance analysis shows which metric evaluation is produce relevant accuracy results in wood quality defect detection.