A Fine-Grained Method for Detecting Defects of Track Fasteners Using RGB-D Image
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9319-2_5
Reference12 articles.
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3. Chandran, P., Asber, J., Thiery, F., Odelius, J., Rantatalo, M.: An investigation of railway fastener detection using image processing and augmented deep learning. Sustainability 13(21), 12051 (2021)
4. Wei, X., Yang, Z., Liu, Y., Wei, D., Jia, L., Li, Y.: Railway track fastener defect detection based on image processing and deep learning techniques: a comparative study. Eng. Appl. Artif. Intell. 80, 66–81 (2019)
5. Peng, Z., Wang, C., Ma, Z., Liu, H.: A Multifeature hierarchical locating algorithm for hexagon nut of railway fasteners. IEEE Trans. Instrum. Meas. 69(3), 693–699 (2020)
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1. Data Fusion of RGB and Depth Data with Image Enhancement;Journal of Imaging;2024-03-21
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