TSW-YOLO-v8n: Optimization of Detection Algorithms for Surface Defects on Sawn Timber

TSW-YOLO-v8n: Optimization of Detection Algorithms for Surface Defects on Sawn Timber

The goal of this work was to better meet the demand for rapid detection of surface defects in sawn timber in forestry production. This paper introduces a two-way feature fusion network based on the YOLO-v8 algorithm and proposes a feature fusion network model that combines the attention mechanism an...

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Bibliographic Details
Main Authors: Mingtao Wang, Mingxi Li, Wenyan Cui, Xiaoyang Xiang, Huaqiong Duo
Format: Article
Language:English
Published: North Carolina State University 2023-10-01
Series:BioResources
Subjects:
deep learning
target detection
surface defects of sawn timber
yolo-v8
attention mechanism
loss function
feature fusion
Online Access:https://ojs.cnr.ncsu.edu/index.php/BRJ/article/view/22962

Internet

https://ojs.cnr.ncsu.edu/index.php/BRJ/article/view/22962

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