An Improved YOLOv5 Algorithm for Wood Defect Detection Based on Attention
Author:
Affiliation:
1. College of Computer and Information Engineering, Central South University of Forestry and Technology, Changsha, China
Funder
Science and Technology Innovation Program of Hunan Province
National Key Research and Development Program of China
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10177807.pdf?arnumber=10177807
Reference38 articles.
1. Wood defects classification using GLCM based features and PSO trained neural network
2. TPH-YOLOv5: Improved YOLOv5 Based on Transformer Prediction Head for Object Detection on Drone-captured Scenarios
3. Feature extraction of wood-hole defects using wavelet-based ultrasonic testing
4. PENet: Object Detection Using Points Estimation in High Definition Aerial Images
5. Wood defect detection method with PCA feature fusion and compressed sensing
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