Results 171 to 180 of about 7,467,907 (193)

DAMF-Net: A Dynamic Receptive Field Enhancement and Semantic-Guided Adaptive Modulated Fusion Network for Steel Surface Defect Segmentation. [PDF]

Sensors (Basel)
Liu D, Chen Z, Zhang C, Cui W, Sun K, Yue B, Zhang L, Li C.   +7 more
europepmc   +1 more source

Study on electromagnetic characteristics of cylindrical hole defect in variable parameter traction motor shaft based on eddy current effect. [PDF]

PLoS One
Song M, Zhu T, Xiao S, Li M, Lai G, Cai Z, Li Q, Xu Z.   +7 more
europepmc   +1 more source

Intelligent Corrosion Sensing and Detection for Aerospace Ground Equipment: A YOLOv11-Based Framework with Shallow Attention and Bidirectional Feature Fusion. [PDF]

Sensors (Basel)
Fang F, Sun D, Geng M, Qu Z, Gu S.
europepmc   +1 more source

ZoomHead: A Flexible and Lightweight Detection Head Structure Design for Slender Cracks. [PDF]

Sensors (Basel)
Li H, Yang F, Huo J, Gao Q, Deng S, Guo C.   +5 more
europepmc   +1 more source

A contribution to reliable rail transport: AI-powered real-time wheel defect detection. [PDF]

Sci Rep
Shaikh MZ, Baro EN, Jatoi S.
europepmc   +1 more source

Microstructure and Dynamic Properties of CrMnFeCoNi(Al)₈ Laser Cladding Coatings on Urban Rail Wheels. [PDF]

Materials (Basel)
Zhang X, Wei P, Wang Y, Chen B, Dong W, Cao X.   +5 more
europepmc   +1 more source

Optimized YOLOv11m for real-time high-speed railway catenary defect detection. [PDF]

Sci Rep
Jin T, Shen Z, Geng H.
europepmc   +1 more source

Failure assessment and evaluation of locomotive coil spring suspension system. [PDF]

Sci Rep
Shanmugam T, Chandran S, Janakiraman R, T KK.   +3 more
europepmc   +1 more source

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

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Self-Supervised Defect Representation Learning for Label-Limited Rail Surface Defect Detection

IEEE Sensors Journal, 2023
Huan Wang, Mingjian Zuo, Zhiliang Liu
exaly