Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization

Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization

Particleboard is an important forest product that can be reprocessed using wood processing by-products. This approach has the potential to achieve significant conservation of forest resources and contribute to the protection of forest ecology. Most current detection models require a significant numb...

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Bibliographic Details
Main Authors: Haifei Xia, Haiyan Zhou, Mingao Zhang, Qingyi Zhang, Chenlong Fan, Yutu Yang, Shuang Xi, Ying Liu
Format: Article
Language:English
Published: MDPI AG 2025-04-01
Series:Sensors
Subjects:
reinforcement learning
particleboard
deep learning
defect detection
Online Access:https://www.mdpi.com/1424-8220/25/8/2541
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