Timber defect identification: Enhanced classification with residual networks
This study investigates the potential enhancement of classification accuracy in timber defect identification through the utilization of deep learning, specifically residual networks. By exploring the refinement of these networks via increased depth and multi-level feature incorporation, the goal is...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Science and Information Organization
2024
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| Online Access: | http://eprints.utem.edu.my/id/eprint/27549/2/0167809052024165055.PDF http://eprints.utem.edu.my/id/eprint/27549/ https://thesai.org/Downloads/Volume15No4/Paper_68-Timber_Defect_Identification.pdf |
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