Results 21 to 30 of about 122,426 (260)
Ensemble model for rail surface defects detection
PLOS ONE, 2022 The detection of rail surface defects is vital for high-speed rail maintenance and management. The CNN-based computer vision approach has been proved to be a strong detection tool widely used in various industrial scenarios. However, the CNN-based detection models are diverse from each other in performance, and most of them require sufficient training ...
Hailang Li +5 more
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Journal of Advanced Mechanical Design, Systems, and Manufacturing, 2023 Bearing surface quality has significant impact on the working performance and durability of the mechanical transmission equipment. The traditional visual detection methods for bearing surface defects face the problems of weak versatility, low efficiency ...
Dan LIANG +4 more
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PLoS ONE, 2023 Automatic detection of surface defects in electronic panels is receiving increasing attention in the quality control of products. The surface defect detection of electronic panels is different from other target detection scenarios and is a meaningful and
Le Wang, Xixia Huang, Zhangjing Zheng
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Segmented Embedded Rapid Defect Detection Method for Bearing Surface Defects
Machines, 2021 The rapid development of machine vision has prompted the continuous emergence of new detection systems and algorithms in surface defect detection. However, most of the existing methods establish their systems with few comparisons and verifications, and ...
Linjian Lei +4 more
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Self-Supervised Railway Surface Defect Detection with Defect Removal Variational Autoencoders
Energies, 2022 In railway surface defect detection applications, supervised deep learning methods suffer from the problems of insufficient defect samples and an imbalance between positive and negative samples.
Yongzhi Min, Yaxing Li
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MeDERT: A Metal Surface Defect Detection Model
IEEE Access, 2023 Defects in various products are unavoidable because of measurement errors and equipment accuracy limitations in the production process. Recent advances in metal surface defect detection have focused on optimizing traditional methods, developing new detection techniques, and exploring deep learning-based algorithms, providing technological support to ...
Chenglong Wang, Heng Xie
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Synthetic Data Generation for Surface Defect Detection
, 2022 Ensuring continued quality is challenging, especially when customer satisfaction is the provided service. It seems to become easier with new technologies like Artificial Intelligence. However, field data are necessary to design an intelligent assistant but are not always available. Synthetic data are used mainly to replace real data.
Lebert, Déborah +4 more
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FS-RSDD: Few-Shot Rail Surface Defect Detection with Prototype Learning
Sensors, 2023 As an important component of the railway system, the surface damage that occurs on the rails due to daily operations can pose significant safety hazards.
Yongzhi Min +3 more
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Deep Active Learning for Surface Defect Detection [PDF]
Sensors, 2020 Most of the current object detection approaches deliver competitive results with an assumption that a large number of labeled data are generally available and can be fed into a deep network at once. However, due to expensive labeling efforts, it is difficult to deploy the object detection systems into more complex and challenging real-world ...
Xiaoming Lv +4 more
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Detection of defects in road surface by a vision system [PDF]
MELECON 2008 - The 14th IEEE Mediterranean Electrotechnical Conference, 2008 This paper presents a real-time method for crack detection used in our apparatus of road characterisation - AMAC . The method based on a set of image processing tasks : bi-level thresholding, morphological operation, and projection. The method have been tested on three kinds of images: the first ones are images taken in laboratory in static mode and ...
Nguyen, Tien Sy +3 more
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