Zeitschriftenartikel zum Thema „Rail area detection“
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Fang, Zhongbin, Xiaojie Huang, Kangquan Ye, et al. "An algorithm for extracting groove rail area based on improved Hough transform." MATEC Web of Conferences 336 (2021): 02025. http://dx.doi.org/10.1051/matecconf/202133602025.
Der volle Inhalt der QuelleChoi, Jung-Youl, and Jae-Min Han. "Deep Learning (Fast R-CNN)-Based Evaluation of Rail Surface Defects." Applied Sciences 14, no. 5 (2024): 1874. http://dx.doi.org/10.3390/app14051874.
Der volle Inhalt der Quelledi Scalea, Francesco Lanza, Ivan Bartoli, Piervincenzo Rizzo, and Mahmood Fateh. "High-Speed Defect Detection in Rails by Noncontact Guided Ultrasonic Testing." Transportation Research Record: Journal of the Transportation Research Board 1916, no. 1 (2005): 66–77. http://dx.doi.org/10.1177/0361198105191600110.
Der volle Inhalt der QuelleWang, Zhangyu, Xinkai Wu, Guizhen Yu, and Mingxing Li. "Efficient Rail Area Detection Using Convolutional Neural Network." IEEE Access 6 (2018): 77656–64. http://dx.doi.org/10.1109/access.2018.2883704.
Der volle Inhalt der QuelleTverdomed, Volodymyr, Anatoliy Gorban, and Lesia Kushmar. "Image segmentation method of rail head defects and area measurement of selected segments." MATEC Web of Conferences 390 (2024): 04008. http://dx.doi.org/10.1051/matecconf/202439004008.
Der volle Inhalt der QuelleLi, Liming, Rui Sun, Shuguang Zhao, Xiaodong Chai, Shubin Zheng, and Ruichao Shen. "Semantic-Segmentation-Based Rail Fastener State Recognition Algorithm." Mathematical Problems in Engineering 2021 (March 2, 2021): 1–15. http://dx.doi.org/10.1155/2021/8956164.
Der volle Inhalt der QuelleShen, Tuo, Jinhuang Zhou, Tengfei Yuan, Yuanxiang Xie, and Xuanxiong Zhang. "LiDAR-Based Urban Three-Dimensional Rail Area Extraction for Improved Train Collision Warnings." Sensors 24, no. 15 (2024): 4963. http://dx.doi.org/10.3390/s24154963.
Der volle Inhalt der QuelleCao, Jinghao, Yang Li, and Sidan Du. "Robust Artificial Intelligence-Aided Multimodal Rail-Obstacle Detection Method by Rail Track Topology Reconstruction." Applied Sciences 14, no. 7 (2024): 2795. http://dx.doi.org/10.3390/app14072795.
Der volle Inhalt der QuelleZheng, Danyang, Liming Li, Shubin Zheng, et al. "A Defect Detection Method for Rail Surface and Fasteners Based on Deep Convolutional Neural Network." Computational Intelligence and Neuroscience 2021 (July 29, 2021): 1–15. http://dx.doi.org/10.1155/2021/2565500.
Der volle Inhalt der QuelleSignore, James M., Mohamed G. Abdel-Maksoud, and Barry J. Dempsey. "Fiber-Optic Sensing Technology for Rail-Buckling Detection." Transportation Research Record: Journal of the Transportation Research Board 1584, no. 1 (1997): 41–45. http://dx.doi.org/10.3141/1584-06.
Der volle Inhalt der QuelleJi, Guoyi, Wen Chen, Jinbai Zou, and Shiyan Wei. "Research on foreign object detection method in track area based on Mask-RCNN." Journal of Physics: Conference Series 2365, no. 1 (2022): 012005. http://dx.doi.org/10.1088/1742-6596/2365/1/012005.
Der volle Inhalt der QuelleHsu, Wei-Lun, and Chia-Ming Chang. "Rail Corrugation Index Development by Sound-Field Excitation on the Carriage Floor of In-Service Train." Sensors 23, no. 17 (2023): 7539. http://dx.doi.org/10.3390/s23177539.
Der volle Inhalt der QuelleRagala, Z., A. Retbi, and S. Bennani. "RAILWAY TRACK FAULTS DETECTION BASED ON IMAGE PROCESSING USING MOBILENET." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W3-2022 (December 2, 2022): 135–41. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w3-2022-135-2022.
Der volle Inhalt der QuelleMauz, Florian, Remo Wigger, Alexandru-Elisiu Gota, and Michal Kuffa. "Automatic Detection of the Running Surface of Railway Tracks Based on Laser Profilometer Data and Supervised Machine Learning." Sensors 24, no. 8 (2024): 2638. http://dx.doi.org/10.3390/s24082638.
Der volle Inhalt der QuelleSeavers, Connor, Guiherme Caselato Gandia, Jackson Winn, James Mathias, Tsuchin Chu, and Anish Poudel. "Line Scanning Thermography for Rail Base Defect Detection." Materials Evaluation 82, no. 11 (2024): 30–40. http://dx.doi.org/10.32548/2024.me-04445.
Der volle Inhalt der QuelleWang, Chensong, Wei Cui, Xingguang Li, and Xinrou Liu. "Foreign Body Detection in the Electrified Area of Urban Rail Trains Using Improved Yolov3 Algorithm." Tobacco Regulatory Science 7, no. 5 (2021): 1059–66. http://dx.doi.org/10.18001/trs.7.5.23.
Der volle Inhalt der QuelleNajya, Hilma, and Ari Purno Wahyu Wibowo. "TECHNOLOGY THE FIRE DETECTION SYSTEM ON THE RAILWAY LINE IS BASED ON IMAGE PROCESSING WITH THE COMPUTER VISION METHOD." Jurnal Darma Agung 31, no. 1 (2023): 65. http://dx.doi.org/10.46930/ojsuda.v31i1.2939.
Der volle Inhalt der QuelleGuo, Long, Jun Zhang, Zhe Chen, et al. "Automatic Detection for Defects of Railroad Track Surface." Applied Mechanics and Materials 278-280 (January 2013): 856–60. http://dx.doi.org/10.4028/www.scientific.net/amm.278-280.856.
Der volle Inhalt der QuelleBersenev, S. P., and E. M. Slobtsova. "Status of nondestructive control of transport function metal products at JSC EVRAZ NTMK." Ferrous Metallurgy. Bulletin of Scientific , Technical and Economic Information 76, no. 6 (2020): 586–90. http://dx.doi.org/10.32339/0135-5910-2020-6-586-590.
Der volle Inhalt der QuelleZhang, Qiang, Fei Yan, Weina Song, Rui Wang, and Gen Li. "Automatic Obstacle Detection Method for the Train Based on Deep Learning." Sustainability 15, no. 2 (2023): 1184. http://dx.doi.org/10.3390/su15021184.
Der volle Inhalt der QuelleSavitha, AC, Kumar KM Madhu, V. Prathap, et al. "Automatic Detection of Obstacle in Railway Track." Journal of Scholastic Engineering Science and Management (JSESM), A Peer Reviewed Universities Refereed Multidisciplinary Research Journal 4, no. 5 (2025): 1–5. https://doi.org/10.5281/zenodo.15385583.
Der volle Inhalt der QuelleKou, Lei, Mykola Sysyn, and Jianxing Liu. "INFLUENCE OF CROSSING WEAR ON ROLLING CONTACT FATIGUE DAMAGE OF FROG RAIL." Facta Universitatis, Series: Mechanical Engineering 22, no. 1 (2024): 025. http://dx.doi.org/10.22190/fume220106024k.
Der volle Inhalt der QuelleLü, Kun Lin, Jun Zhang, Guang Yu Dai, et al. "Track Surface Image Collecting System Base on Area-Array Camera." Applied Mechanics and Materials 321-324 (June 2013): 1145–49. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.1145.
Der volle Inhalt der QuellePhrommahakul, Nichapa, Manwika Kongpuang, Suhaidee Sani, Anas Katib, and Fittriya Sulong. "Detection of Rail Defects Using Phased Array Ultrasonic Technique." E3S Web of Conferences 602 (2025): 01009. https://doi.org/10.1051/e3sconf/202560201009.
Der volle Inhalt der QuelleFang, Bo, Cheng Qiu, Ming Feng, Wei Liang, and Ximing Zhang. "Collision Avoidance Strategy for Multivehicle Conflict on Common Rail." Mathematical Problems in Engineering 2022 (May 3, 2022): 1–14. http://dx.doi.org/10.1155/2022/9388092.
Der volle Inhalt der QuelleZhang, Ziwen, Mangui Liang, and Zhiyu Liu. "A Novel Decomposition Model for Visual Rail Surface Inspection." Electronics 10, no. 11 (2021): 1271. http://dx.doi.org/10.3390/electronics10111271.
Der volle Inhalt der QuelleKuzmin, Egor V., Oleg E. Gorbunov, Petr O. Plotnikov, Vadim A. Tyukin, and Vladimir A. Bashkin. "Application of Neural Networks for Recognizing Rail Structural Elements in Magnetic and Eddy Current Defectograms." Modeling and Analysis of Information Systems 25, no. 6 (2018): 667–79. http://dx.doi.org/10.18255/1818-1015-2018-6-667-679.
Der volle Inhalt der QuelleSakthivel, V. "Advanced IoT Solution for Early Detection of Railway Hazards." International Journal for Research in Applied Science and Engineering Technology 13, no. 4 (2025): 4873–76. https://doi.org/10.22214/ijraset.2025.69363.
Der volle Inhalt der QuelleChandran, Praneeth, Johnny Asber, Florian Thiery, Johan Odelius, and Matti Rantatalo. "An Investigation of Railway Fastener Detection Using Image Processing and Augmented Deep Learning." Sustainability 13, no. 21 (2021): 12051. http://dx.doi.org/10.3390/su132112051.
Der volle Inhalt der QuelleSimonović, Miloš, Milan Banić, Dušan Stamenković, et al. "Toward the Enhancement of Rail Sustainability: Demonstration of a Holistic Approach to Obstacle Detection in Operational Railway Environments." Sustainability 16, no. 7 (2024): 2613. http://dx.doi.org/10.3390/su16072613.
Der volle Inhalt der QuelleCao, Xiangang, Mengzhen Zuo, Guoyin Chen, Xudong Wu, Peng Wang, and Yizhe Liu. "Visual Localization Method for Fastener-Nut Disassembly and Assembly Robot Based on Improved Canny and HOG-SED." Applied Sciences 15, no. 3 (2025): 1645. https://doi.org/10.3390/app15031645.
Der volle Inhalt der QuelleHanum, Arrosida, Susanto Agus, Ciptaningrum Adiratna, Rudianti Tyan, Nazar Surya Kencana Masayu, and Mahmud Rizal. "Rail Line Surfaces Defect Monitoring using YOLO Architecture: Case Study on Madiun-Magetan Track, East Java." Rail Line Surfaces Defect Monitoring using YOLO Architecture: Case Study on Madiun-Magetan Track, East Java 8, no. 12 (2023): 15. https://doi.org/10.5281/zenodo.10432573.
Der volle Inhalt der QuelleWang, Yi, Yuhui Wang, Ping Wang, et al. "Rail Magnetic Flux Leakage Detection and Data Analysis Based on Double-Track Flaw Detection Vehicle." Processes 11, no. 4 (2023): 1024. http://dx.doi.org/10.3390/pr11041024.
Der volle Inhalt der QuelleBai, Tangbo, Jialin Gao, Jianwei Yang, and Dechen Yao. "A Study on Railway Surface Defects Detection Based on Machine Vision." Entropy 23, no. 11 (2021): 1437. http://dx.doi.org/10.3390/e23111437.
Der volle Inhalt der QuelleWang, Nan, Tao Hou, and Tianming Zhang. "Research on railway track edge detection based on BM3D and Zernike moments." Archives of Transport 68, no. 4 (2023): 7–20. http://dx.doi.org/10.61089/aot2023.fz9g6c16.
Der volle Inhalt der QuelleYe, Xuan-Yu, Yan-Yun Luo, Zai-Wei Li, and Xiao-Zhou Liu. "A Quantitative Detection Method for Surface Cracks on Slab Track Based on Infrared Thermography." Applied Sciences 13, no. 11 (2023): 6681. http://dx.doi.org/10.3390/app13116681.
Der volle Inhalt der QuelleEsteves, Gonçalo, Filipe Fidalgo, Nuno Cruz, and José Simão. "Long-Range Wide Area Network Intrusion Detection at the Edge." IoT 5, no. 4 (2024): 871–900. https://doi.org/10.3390/iot5040040.
Der volle Inhalt der QuellePan, Yucheng, Jiasi Chen, Peiwen Wu, Hongsheng Zhong, Zihao Deng, and Daozong Sun. "Enhanced Rail Surface Defect Segmentation Using Polarization Imaging and Dual-Stream Feature Fusion." Sensors 25, no. 11 (2025): 3546. https://doi.org/10.3390/s25113546.
Der volle Inhalt der QuelleMogyla, V. I., M. O. Morneva, and M. V. Kovtanets. "The use of the multivariate antiskid sensor to gain maximum trailed load of the rolling stock." Вісник Східноукраїнського національного університету імені Володимира Даля, no. 5 (275) (December 10, 2022): 55–57. http://dx.doi.org/10.33216/1998-7927-2022-275-5-55-57.
Der volle Inhalt der QuelleChudzikiewicz, Andrzej, Jozef Drozdziel, and Bogdan Sowinski. "Practical Solution of Rail Vehicle and Track Dynamics Monitoring System." Key Engineering Materials 518 (July 2012): 271–80. http://dx.doi.org/10.4028/www.scientific.net/kem.518.271.
Der volle Inhalt der QuelleLiu, Shuai, Yu-Hao Shi, Tian-Yu Lin, Yong-Peng Zhang, Zhi-Jian Lu, and Lan-Jun Yang. "Influence of operating parameters on discharge mode of parallel-rail accelerator." Acta Physica Sinica 70, no. 20 (2021): 205205. http://dx.doi.org/10.7498/aps.70.20210484.
Der volle Inhalt der QuelleLiu, Shuai, Yu-Hao Shi, Tian-Yu Lin, Yong-Peng Zhang, Zhi-Jian Lu, and Lan-Jun Yang. "Influence of operating parameters on discharge mode of parallel-rail accelerator." Acta Physica Sinica 70, no. 20 (2021): 205205. http://dx.doi.org/10.7498/aps.70.20210484.
Der volle Inhalt der QuelleXiao, Tianwen, Yongneng Xu, and Huimin Yu. "Research on Obstacle Detection Method of Urban Rail Transit Based on Multisensor Technology." Journal of Artificial Intelligence and Technology 1, no. 1 (2021): 61–67. http://dx.doi.org/10.37965/jait.2020.0027.
Der volle Inhalt der QuelleYuan, Cheng, and Xin Chen. "Research on collision avoidance method based on millimeter wave radar." Highlights in Science, Engineering and Technology 37 (March 18, 2023): 137–41. http://dx.doi.org/10.54097/hset.v37i.6068.
Der volle Inhalt der QuellePamuła, Teresa, and Wiesław Pamuła. "Detection of Safe Passage for Trains at Rail Level Crossings Using Deep Learning." Sensors 21, no. 18 (2021): 6281. http://dx.doi.org/10.3390/s21186281.
Der volle Inhalt der QuelleMa, Boyang, Shupeng Chen, Shulong Wang, et al. "A False Trigger-Strengthened and Area-Saving Power-Rail Clamp Circuit with High ESD Performance." Micromachines 14, no. 6 (2023): 1172. http://dx.doi.org/10.3390/mi14061172.
Der volle Inhalt der QuelleJia, Yajuan, Jianbo Zheng, and Hongfang Zhou. "Research on Airborne Electromagnetic Whole-area Apparent Resistivity Imaging Algorithm in the Detection of Goaf in Rail Transit." Journal of Physics: Conference Series 2083, no. 4 (2021): 042072. http://dx.doi.org/10.1088/1742-6596/2083/4/042072.
Der volle Inhalt der QuelleYaodong, Jiang. "Active Obstacle Detection System Based on Video Recognition and Lidar Information Fusion." New Metro 1, no. 1 (2020): 11–21. http://dx.doi.org/10.37819/nm.001.01.0073.
Der volle Inhalt der QuelleJiang, Aihui, Jie Dai, Sisi Yu, Baolei Zhang, Qiaoyun Xie, and Huanxue Zhang. "Unsupervised Change Detection around Subways Based on SAR Combined Difference Images." Remote Sensing 14, no. 17 (2022): 4419. http://dx.doi.org/10.3390/rs14174419.
Der volle Inhalt der QuelleBeauchamp, A. J. "Banded rail (Gallirallus philippensis) detection at Ruakaka estuary before, during, and after mangrove (Avicennia marina) removal." Notornis 72, no. 3 (2025): 161. https://doi.org/10.63172/012836krmcgh.
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