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Research Progress of Visual Inspection Technology of Steel Products—A Review

Xiaohong Sun, Jinan Gu, Shixi Tang, Jing Li
2018 Applied Sciences  
At present, visual inspection technology based on image processing has an absolute advantage because of its intuitive nature, convenience, and efficiency.  ...  The network framework based on deep learning provides space for the development of end-to-end mode inspection technology, which would greatly promote the implementation of intelligent manufacturing.  ...  Strengths and weaknesses of machine learning-based detection methods for steel defects.  ... 
doi:10.3390/app8112195 fatcat:g2cl62arh5bnlg76fesmldhlja

Visual-Based Defect Detection and Classification Approaches for Industrial Applications—A SURVEY

Tamás Czimmermann, Gastone Ciuti, Mario Milazzo, Marcello Chiurazzi, Stefano Roccella, Calogero Maria Oddo, Paolo Dario
2020 Sensors  
We continue with a survey of textural defect detection based on statistical, structural and other approaches.  ...  Finally, we report the state of the art for approaching the detection and classification of defects through supervised and non-supervised classifiers and deep learning.  ...  a defect detection method based on semantic segmentation.  ... 
doi:10.3390/s20051459 pmid:32155900 fatcat:rsdnszztffbadllniclol3pjvi

Weakly Supervised Acoustic Defect Detection in Concrete Structures Using Clustering-based Augmentation

Jun Younes Louhi Kasahara, Hiromitsu Fujii, Atsushi Yamashita, Hajime Asama
2021 IEEE/ASME transactions on mechatronics  
In this paper, we propose a novel approach for weakly supervised acoustic defect detection in concrete structures that augments human-provided weak supervision.  ...  Weakly supervised approaches, i.e., approaches based on supervision in other forms than traditional class labels, offer a unique mix of automation and human involvement that is highly effective for critical  ...  Our contributions are as follows: • A novel concept aiming to augment weak supervision for defect detection in concrete structures, based on both unsupervised clustering and human-provided weak supervision  ... 
doi:10.1109/tmech.2021.3077496 fatcat:h4ujvtdhsjbvzd7hgdfgosp774

State of the Art in Defect Detection Based on Machine Vision

Zhonghe Ren, Fengzhou Fang, Ning Yan, You Wu
2021 International Journal of Precision Engineering and Manufacturing - Green Technology  
The latest developments in industrial defect detection based on machine vision are introduced.  ...  AbstractMachine vision significantly improves the efficiency, quality, and reliability of defect detection.  ...  Although machine vision technology may not be perfect, defect detection based on machine vision is still the main direction for future research and development in this area.  ... 
doi:10.1007/s40684-021-00343-6 fatcat:gzukmfsx3veexktu2mg4tcbdfi

Weakly supervised network based intelligent identification of cracks in asphalt concrete bridge deck

Jinsong Zhu, Jinbo Song
2020 Alexandria Engineering Journal  
Thirdly, the cracks in the bridge deck defects images were subjected to semantic segmentation under weak supervision.  ...  However, the conventional crack detection methods cannot identify the defects on asphalt concrete bridge deck accurately and efficiently, due to the dark color of the deck and the complexity, different  ...  Finally, the cracks in the images on bridge deck defects were subjected to semantic segmentation under weak supervision.  ... 
doi:10.1016/j.aej.2020.02.027 fatcat:6untmmms65f5bjtrfbgfm7wemi

A Survey of Surface Defect Detection of Industrial Products Based on A Small Number of Labeled Data [article]

Qifan Jin
2022 arXiv   pre-print
fine-tuning, semi-supervised, weak supervised and unsupervised.  ...  Deep learning-based industrial product surface defect detection methods suitable for a small number of labeled data are divided into based on data augmentation, based on transfer learning, model-based  ...  Weak Supervision Weak supervision uses data with unreliable labels to train surface defect detection models.  ... 
arXiv:2203.05733v1 fatcat:7imwu76dqzglvms4fivggd6r3y

A Survey on Recent Applications of Machine Learning with Big Data in Additive Manufacturing Industry

Micheal Omotayo Alabi, Ken Nixon, Ionel Botef
2018 American Journal of Engineering and Applied Sciences  
This paper explores recent applications of Machine Learning with Big Data in the field of additive manufacturing, for instance, application of machine learning in detecting defect or anomaly during build  ...  Machine Learning is a growing field of Artificial Intelligence (AI) that allows systems to learn from data, identify patterns and make decisions with very little human involvement.  ...  However, the corresponding author secure a funding for his current postgraduate program through SITA Inc. UK Ltd.  ... 
doi:10.3844/ajeassp.2018.1114.1124 fatcat:sjohrqgje5gsxmt7sbeps5rr5y

Research Progress of Automated Visual Surface Defect Detection for Industrial Metal Planar Materials

Xiaoxin Fang, Qiwu Luo, Bingxing Zhou, Congcong Li, Lu Tian
2020 Sensors  
The computer-vision-based surface defect detection of metal planar materials is a research hotspot in the field of metallurgical industry.  ...  This paper attempts to present a comprehensive survey on both two-dimensional and three-dimensional surface defect detection technologies based on reviewing over 160 publications for some typical metal  ...  With the rapid development of machine vision technology, the automated surface defect detection methods based on machine vision have gradually become the mainstream methods and have been widely used in  ... 
doi:10.3390/s20185136 pmid:32916943 fatcat:qele6iuawnayrkjwywhkhjrmae

Review of Industry Workpiece Classification and Defect Detection using Deep Learning

Changxing Chen, Azween Abdullah, S. H. Kok, D. T. K. Tien
2022 International Journal of Advanced Computer Science and Applications  
Object detection and classification denotes one of the most extensively-utilized machine vision applications given the high requirements put forward for object classification and defect detection with  ...  As a branch of machine learning, deep learning has attained more optimal results in the image recognition discipline.  ...  Every picture encompassed the images saved in grayscale 8-bit PNG format for weak supervised industrial optical detection learning and training.  ... 
doi:10.14569/ijacsa.2022.0130439 fatcat:p37gspzvm5cihimp7u7tawjqmm

Computer Vision Analysis on Material Characterization Images

Danpeng Cheng, Wuxin Sha, Zuo Xu, Lixin Huang, Yunpeng Du, Shun Tang, Yaqing Guo, Yuan-Cheng Cao, Shijie Cheng
2021 Advanced Intelligent Systems  
on machine vision.  ...  Grain and texture segmentation with computer vision. a) An encode-decoder based network to detect defects that break lattice periodicity.  ... 
doi:10.1002/aisy.202100158 fatcat:2ioo7gan5bhwdptp2r5dxtsdz4

Table of Content

2020 2020 International Conference on Convergence to Digital World - Quo Vadis (ICCDW)  
Gravitator -A gravity based power generator 20. Technical Analysis Test for a Weak-form of Efficient Market Hypothesis 21.  ...  Methods of High-Density Plasma Generation 68. FederatedLearning -A Review 69. Design a microstrip patch 5G antenna with modified defective ground structure 70.  ... 
doi:10.1109/iccdw45521.2020.9318647 fatcat:bo2do2o2tfdwnb4s5y57wh4mvq

The Use of Artificial Intelligence-Based Optical Remote Sensing and Positioning Technology in Microelectronic Processing Technology

Chenqi Yan, Mengchao Tan, Narasimhan Venkateswaran
2021 Wireless Communications and Mobile Computing  
A new optical remote sensing-optical beam induced resistance change (ORS-OBIRCH) target recognition and location defect detection method is proposed based on an artificial intelligence algorithm, optical  ...  Simulation results show that this method can quickly reduce the detection range and locate defects accurately and efficiently.  ...  learning, weak supervised learning, and semisupervised learning [21] .  ... 
doi:10.1155/2021/8464612 fatcat:re7tiu2o7nf4pens54cnc2zidi

Perovskite-Based Memristor with 50-Fold Switchable Photosensitivity for In-Sensor Computing Neural Network

Qilai Chen, Tingting Han, Jianmin Zeng, Zhilong He, Yulin Liu, Jinglin Sun, Minghua Tang, Zhang Zhang, Pingqi Gao, Gang Liu
2022 Nanomaterials  
In-sensor computing can simultaneously output image information and recognition results through in-situ visual signal processing, which can greatly improve the efficiency of machine vision.  ...  –750 nm), and peak responsibility value at 750 nm reaches 0.45 A/W.  ...  (a) Schematic diagram of the vision-enhanced in-sensor computing neural network; (b) schematic flowchart for the supervised learning simulation with artificial neural network for high-fidelity imaging  ... 
doi:10.3390/nano12132217 pmid:35808058 pmcid:PMC9268359 fatcat:5l7oowsjtvaflbnekygj5zdbaq

Using Deep Learning to Detect Defects in Manufacturing: A Comprehensive Survey and Current Challenges

Jing Yang, Shaobo Li, Zheng Wang, Hao Dong, Jun Wang, Shihao Tang
2020 Materials  
Third, we summarize and analyze the application of ultrasonic testing, filtering, deep learning, machine vision, and other technologies used for defect detection, by focusing on three aspects, namely method  ...  Lastly, we outline the current achievements and limitations of the existing methods, along with the current research challenges, to assist the research community on defect detection in setting a further  ...  The defect-detection methods are based on filtering has a strong ability to describe the disturbance signal and detection of the tool defect inside the machine.  ... 
doi:10.3390/ma13245755 pmid:33339413 pmcid:PMC7766692 fatcat:egyrdqjmqvebvoeaqf5yyi3cxm

Artificial intelligence based defect classification for weld joints

S Esther Florence, R Vimal Samsingh, Vimaleswar Babureddy
2018 IOP Conference Series: Materials Science and Engineering  
This paper mainly deals with the development of a defect classification system that uses Artificial Neural Network (ANN) to classify weld defects based on ultrasonic test data.  ...  The study mainly consists of three parts-(i) Weld defect detection using Ultrasonic Testing (UT) (ii) Implementation of ANN (iii) Defect classification.  ...  Learning methods Supervised machine learning is the formulation of a function based on labelled training data. The training data consist of sample data whose characteristics are known.  ... 
doi:10.1088/1757-899x/402/1/012159 fatcat:3p4zhzjd3vdb7ivjvlivl2nwr4
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