Wood Defect Inspection on Dead Knots and Pinholes Using YOLOv5x Algorithm
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9005-4_74
Reference7 articles.
1. Kryl M, Danys L, Jaros R, Martinek R, Kodytek P, Bilik P (2020) Wood recognition and quality imaging inspection systems. J Sens 2020. https://doi.org/10.1155/2020/3217126
2. Deng ZY, Wang YZ, Zhang HR (2020) Detection method of wood skin defects based on bag-of-words model. In: ACM international conference proceeding series. Association for computing machinery, Oct 2020, pp 125–130. https://doi.org/10.1145/3438872.3439068
3. Chun TH et al (2021) Identification of wood defect using pattern recognition technique. Int J Adv Intell Inform 7(2):163–176. https://doi.org/10.26555/ijain.v7i2.588
4. Zhang Y, Jiang D, Zhang Z, Chen J (2022) Three-dimensional inversion of knot defects recognition in timber cutting. J For Res. https://doi.org/10.1007/s11676-022-01532-y
5. He T, Liu Y, Yu Y, Zhao Q, Hu Z (2020) Application of deep convolutional neural network on feature extraction and detection of wood defects. Measurement 152. https://doi.org/10.1016/j.measurement.2019.107357
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