Research on Rail Diseases Detection Algorithm Based on Deep Learning
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Published:2023
Issue:04
Volume:12
Page:340-350
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ISSN:2326-3415
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Container-title:Artificial Intelligence and Robotics Research
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language:
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Short-container-title:AIRR
Publisher
Hans Publishers
Subject
Earth-Surface Processes
Reference28 articles.
1. 王建柱, 李清勇, 张靖, 等. 轨道病害视觉检测: 背景、方法与趋势[J]. 中国图象图形学报, 2021, 26(2): 287-296.
2. Faghih-Roohi, S., Hajizadeh, S., Núñez, A., Babuska, R. and De Schutter, B. (2016) Deep Convolutional Neural Networks for Detection of Rail Surface Defects. Proceedings of 2016 International Joint Conference on Neural Networks, 24-29 July 2016, 2584-2589.
3. Dong, B.Y., Li, Q.Y., Wang, J.Z., Huang, W., Dai, P. and Wang, S.C. (2019) An End-to-End Abnormal Fastener Detection Method Based on Data Synthesis. Proceedings of the 31st IEEE International Conference on Tools with Artificial Intelligence, 4-6 November 2019, 149-156.
4. A fast template matching-based algorithm for railway bolts detection