Wood Surface Defects Detection Based on the Improved YOLOv5-C3Ghost With SimAm Module
The detection of defects in wood is valuable for promoting the efficient exploitation of wood. So it is significant to further increase the accuracy of the detection of wood defects and enhance the real-time detection. In this paper, the YOLOv5 convolutional neural network is applied to wood defects...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10214278/ |