标题
Automatic railroad track components inspection using real‐time instance segmentation
作者
关键词
-
出版物
COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
Volume -, Issue -, Pages -
出版商
Wiley
发表日期
2020-09-25
DOI
10.1111/mice.12625
参考文献
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- (2020) Xiao Pan et al. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
- Modelling of the pavement acoustic longevity in Hong Kong through machine learning techniques
- (2020) Ruijun Cao et al. TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
- Automatic pixel-level multiple damage detection of concrete structure using fully convolutional network
- (2019) Shengyuan Li et al. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
- A unified convolutional neural network integrated with conditional random field for pipe defect segmentation
- (2019) Mingzhu Wang et al. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
- Convolutional neural network-based wind-induced response estimation model for tall buildings
- (2019) Byung Kwan Oh et al. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
- Concrete crack detection using context‐aware deep semantic segmentation network
- (2019) Xinxiang Zhang et al. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
- Densely Pyramidal Residual Network for UAV-based Railway Images Dehazing
- (2019) Yunpeng Wu et al. NEUROCOMPUTING
- Concrete bridge surface damage detection using a single‐stage detector
- (2019) Chaobo Zhang et al. COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
- Pixel-Level Cracking Detection on 3D Asphalt Pavement Images Through Deep-Learning- Based CrackNet-V
- (2019) Yue Fei et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- Res2Net: A New Multi-Scale Backbone Architecture
- (2019) Shang-Hua Gao et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- A novel unsupervised deep learning model for global and local health condition assessment of structures
- (2018) Mohammad Hossein Rafiei et al. ENGINEERING STRUCTURES
- Automated region-of-interest localization and classification for vision-based visual assessment of civil infrastructure
- (2018) Chul Min Yeum et al. STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL
- A UAV-Based Visual Inspection Method for Rail Surface Defects
- (2018) Yunpeng Wu et al. Applied Sciences-Basel
- Image-based post-disaster inspection of reinforced concrete bridge systems using deep learning with Bayesian optimization
- (2018) Xiao Liang COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING
- Recurrent neural network model with Bayesian training and mutual information for response prediction of large buildings
- (2018) Carlos A. Perez-Ramirez et al. ENGINEERING STRUCTURES
- Deep Multitask Learning for Railway Track Inspection
- (2017) Xavier Gibert et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- A novel machine learning-based algorithm to detect damage in high-rise building structures
- (2017) Mohammad Hossein Rafiei et al. STRUCTURAL DESIGN OF TALL AND SPECIAL BUILDINGS
- Deep learning
- (2015) Yann LeCun et al. NATURE
- Railway Fastener Inspection by Real-Time Machine Vision
- (2015) Caglar Aytekin et al. IEEE Transactions on Systems Man Cybernetics-Systems
- Automatic Fastener Classification and Defect Detection in Vision-Based Railway Inspection Systems
- (2013) Hao Feng et al. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
- Automated Visual Inspection of Railroad Tracks
- (2013) Esther Resendiz et al. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
- A Real-Time Visual Inspection System for Discrete Surface Defects of Rail Heads
- (2012) Qingyong Li et al. IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
- An Efficient Direction Field-Based Method for the Detection of Fasteners on High-Speed Railways
- (2011) Jinfeng Yang et al. SENSORS
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