THE PROSPECT OF ARTIFICIAL INTELLIGENCE- BASED WOOD SURFACE INSPECTION

Authors

  • Yalamandala Vinod
  • Vadlamudi Chaitanya
  • Saladi Raghavendra Sai
  • Sangepu Sreekanth
  • Ms. S. Saranya

Keywords:

wood defect detection, deep learning, convolutional neural networks, transfer learning, quality control, woodworking industry

Abstract

Identifying wood errors is an essential part of the production process because the woodworking business is very dependent on the final wood products that meet quality standards. This has always been a labor -intensive process that requires experienced individuals physically verify each element. But new opportunities for automatic and improvement to detect wood errors have emerged as intensive learning algorithms have improved.

 

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Published

2025-09-17

How to Cite

Yalamandala Vinod, Vadlamudi Chaitanya, Saladi Raghavendra Sai, Sangepu Sreekanth, & Ms. S. Saranya. (2025). THE PROSPECT OF ARTIFICIAL INTELLIGENCE- BASED WOOD SURFACE INSPECTION. Utilitas Mathematica, 122(2), 1068–1077. Retrieved from https://utilitasmathematica.com/index.php/Index/article/view/2819

Issue

Vol. 122 No. 2 (2025): Vol. 122 No. 2 (2025): Volume 122, 2025

Section

Articles

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