Results 21 to 30 of about 326,783 (293)

TSDNet: A New Multiscale Texture Surface Defect Detection Model

Applied Sciences, 2023
Industrial defect detection methods based on deep learning can reduce the cost of traditional manual quality inspection, improve the accuracy and efficiency of detection, and are widely used in industrial fields.
Min Dong, Dezhen Li, Kaixiang Li, Junpeng Xu   +3 more
doaj   +1 more source

YOLOv4-MN3 for PCB Surface Defect Detection

Applied Sciences, 2021
Surface defect detection for printed circuit board (PCB) is indispensable for managing PCB production quality. However, automatic detection of PCB surface defects is still a challenging task because, even within the same category of surface defect ...
Xinting Liao, Shengping Lv, Denghui Li, Yong Luo, Zichun Zhu, Cheng Jiang   +5 more
doaj   +1 more source

Defect detection of bearing side face based on sample data augmentation and convolutional neural network

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, Ding Cai WANG, Jia Le CHU, Kai HU, Yong Long XI   +4 more
doaj   +1 more source

Online Metallic Surface Defect Detection Using Deep LearningOnline Metallic Surface Defect Detection Using Deep Learning [PDF]

, 2020
Abstract Across a range of manufacturing contexts, automated quality control has been gaining significantattention because it offers competitive advantages such as cost reduction, high accuracy in defect detection, and system stability over time.
Feyza ÇEREZCİ, Serap KAZAN, Muhammed Ali Oz, Cemil Oz, Tugrul Tasci, Selman Hızal, Çağlayan Altay   +6 more
openaire   +1 more source

Backside delamination detection in composites through local defect resonance induced nonlinear source behavior [PDF]

, 2020
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Hedayatrasa, Saeid, Kersemans, Mathias, Poelman, Gaétan, Segers, Joost, Van Paepegem, Wim   +4 more
core   +2 more sources

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, Shengli Sun, Yue Zhang, Huikai Liu, Hui Xie   +4 more
doaj   +1 more source

Surface defect detection method for electronic panels based on attention mechanism and dual detection heads.

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
doaj   +1 more source

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
doaj   +1 more source

An initial investigation on the potential applicability of Acoustic Emission to rail track fault detection. [PDF]

, 2004
In light of recent accidents in the rail industry, the assessment of the mechanical integrity of rail-track is of vital importance. This encompasses the integrity of the track due to rolling contact fatigue and surface wear. Whilst numerous techniques
Bruzelius, Kristoffer, Mba, David
core   +1 more source

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, Ziwei Wang, Yang Liu, Zheng Wang   +3 more
doaj   +1 more source