Results 181 to 190 of about 5,176,577 (228)

Monolithic integration of p- and n-type doped 2D WSe₂ for wafer-scale complementary logic circuits. [PDF]

Nat Commun
Hu Y, Zeng S, Wang Y, Zhang J, Zhu Y, Zhang Z, Dong X, Sun Q, Ao M, Guo X, Shang J, Wang Y, Liu C, Tian Y, Chen H, He X, Song Y, Zhang Y, Wang S, Shi J, Sun Z, Wang J, Li J, Jiang L, Wang L, Zhu C, Xu Z, Gou S, Wang Y, Xia Y, Wang X, Sun Z, Bao W.   +32 more
europepmc   +1 more source

TDRPFormer: Texture-Debiased Reliable Prototype Transformer for Pixel-Level Steel Surface Defect Segmentation. [PDF]

Sensors (Basel)
Zhu M, Li Z, Sun H, Wang Y, Wang J.
europepmc   +1 more source

A defect recognition method based on ITLPP and multi-feature fusion matrix. [PDF]

Sci Rep
Lei B, Yi P.
europepmc   +1 more source

Automatic 3D railroad alignment detection using modified Hough transform. [PDF]

Sci Rep
Lee J, Park J, Shin H, Yoon H.
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Failure Analysis of Gear on Rail Transit. [PDF]

Materials (Basel)
Pan AX, Wen C, Wang H, Tao P, Liu X, Gong Y, Yang ZG.   +6 more
europepmc   +1 more source

MCM-YOLO: A Lightweight Conflict Mitigation Network for Industrial Metal Surface Defect Detection. [PDF]

Sensors (Basel)
Zhang S, He K, Xu J, Sha H, Chen Z.
europepmc   +1 more source

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A Large-Model-Enhanced Method for Rail Surface Defect Detection in Heavy-Haul Railway

IEEE Transactions on Intelligent Transportation Systems
The rail surface defects directly impact the safety and efficiency of heavy-haul train operations. Timely assessment of these defects is crucial for informed maintenance decisions, with precise defect detection at its core.
Yongkui Sun, Yuan Cao, Shuai Su
exaly   +2 more sources

Deep Learning and Laser-Based 3-D Pixel-Level Rail Surface Defect Detection Method

IEEE Transactions on Instrumentation and Measurement, 2023
Rail surface defect inspection is of particular importance in modern railways. Accurate and efficient surface defect detection approaches support optimized maintenance. This enables the safe operation of the railway network.
Qianyu Chen, Clive Roberts, Yaguo Lei
exaly   +2 more sources

Rail Surface Defect Detection Based on Image Enhancement and Improved YOLOX

Electronics (Switzerland), 2023
During the long and high-intensity railway use, all kinds of defects emerge, which often produce light to moderate damage on the surface, which adversely affects the stable operation of trains and even endangers the safety of travel.
Wu Deng
exaly   +2 more sources

FHENet: Lightweight Feature Hierarchical Exploration Network for Real-Time Rail Surface Defect Inspection in RGB-D Images

IEEE Transactions on Instrumentation and Measurement, 2023
In recent years, computer vision systems have been increasingly applied to rail defect inspection. Rail defects should be identified quickly and accurately to ensure safe, stable, and fast train operations and thereby reduce the incidence of accidents ...
Wu-Jie Zhou, Jian-ping Hong
semanticscholar   +1 more source