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Relevant bibliographies by topics / Defects classification

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Academic literature on the topic 'Defects classification'

Author: Grafiati

Published: 28 June 2021

Last updated: 29 July 2025

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Journal articles on the topic "Defects classification"

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Nurlaelah, Azis, and Usman Sudjadi. "The Classification of Residential Defects (Case Study: Citra Garden Residence in Indonesia)." Applied Mechanics and Materials 507 (January 2014): 97–106. http://dx.doi.org/10.4028/www.scientific.net/amm.507.97.

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The classification of residential defects (case study: Citra Garden Residence in Indonesia) was studied. This study aims to more satisfied customers. The study begins with the literature review to formulate the classification of house defects. Then classify the defect of house into two, namely the classification of house defects based on period of post hand over, and the classification of house defects based on category of the defects. Further studies followed by dividing the classification of house defects based on period of post-hand over into three parts, namely before hand over period (inv

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Huh, Sang Moo, and Woo-Je Kim. "The Derivation of Defect Priorities and Core Defects through Impact Relationship Analysis between Embedded Software Defects." Applied Sciences 10, no. 19 (2020): 6946. http://dx.doi.org/10.3390/app10196946.

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As embedded software is closely related to hardware equipment, any defect in embedded software can lead to major accidents. Thus, all defects must be collected, classified, and tested based on their severity. In the pure software field, a method of deriving core defects already exists, enabling the collection and classification of all possible defects. However, in the embedded software field, studies that have collected and categorized relevant defects into an integrated perspective are scarce, and none of them have identified core defects. Therefore, the present study collected embedded softw

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Pond, R. C. "TEM studies of line defects in interfaces." Proceedings, annual meeting, Electron Microscopy Society of America 46 (1988): 586–87. http://dx.doi.org/10.1017/s0424820100104996.

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Line defects are ubiquitious features in interfaces, and have important structural and mechanistic role. Recently, a crystallographic theory of such defects has been presented which appears to offer a comprehensive framework for their classification. The object of the present paper is firstly to outline the characterisation and classification of defects according to this treatment. Secondly, we illustrate examples of defects in the distinctive classes observed using tern, and discuss the various imaging techniques which have been employed.In the absence of a rigorous treatment of line defects

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Du Rand, Francois, Malan Van Tonder, Andre Van Der Merwe, et al. "Powder Bed Defects Classification: An Industry Perspective." MATEC Web of Conferences 370 (2022): 06003. http://dx.doi.org/10.1051/matecconf/202237006003.

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The manufacture of defect-free parts has been a key discussion topic with the widespread adoption of additive manufacturing by industry. While significant research has been performed on the detection of powder bed defects, the focus has been on the classification of the defects according to defect type. However, when looking at creating a closed loop feedback system, it is important for the machine to make autonomous decisions regarding defects. The focus of this paper will be to create a defect severity classification matrix based on industry partner experience as well as published literature

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Cho, Du Hyung, and Seok Lyong Lee. "Defect Identification and Classification for Plasma Display Panels." Advanced Materials Research 694-697 (May 2013): 1197–201. http://dx.doi.org/10.4028/www.scientific.net/amr.694-697.1197.

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The defect inspection is a crucial process for the plasma display panel (PDP) production that significantly influences the quality of final products. In this paper, we propose a defect identification and classification method that extracts and classifies defects using various image analysis techniques. First, we identify defects through binarization of images using Gaussian filter. Then, those defects are classified into seven different types by analyzing geometric characteristics of defects and utilizing a support vector machine (SVM) classifier. The experimental results using separate sets o

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Ivanov, S. A. "CLASSIFICATION DEFECTS IN THE LOWER LIP." Health and Ecology Issues, no. 2 (June 28, 2005): 89–92. http://dx.doi.org/10.51523/2708-6011.2005-2-2-18.

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The systematizing of defects of the lower lip following resection helps to choose the optimal choice of the cheiloplasty. We have analyzed the patients group including 144 reconstructions of lower lip. We have worked out the classification of the defects in the lower lip. It is adapted to the modern TNM-staging of malignant tumors. The defects following T1-tumor excision are corresponding to less than 1/3 of lip, the defects following T2-tumor excision are corresponding to 1/3-1/2 of lip, the defects following T1-tumor excision are corresponding to more then 1/2 of lip. There are included the

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Liu, Shujie. "Classification of Tobacco Defects based on Vgg16." Academic Journal of Science and Technology 12, no. 2 (2024): 26–27. http://dx.doi.org/10.54097/mmeyx924.

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In the existing cigarette packet defect detection using simple image processing methods, the defect detection capability is limited and the corresponding defects cannot be counted. This paper addresses this problem and proposes a vgg16-based defect classification method for cigarette packets, which can effectively detect and count the defects of cigarette packets. Experiments have proved that the detection accuracy can reach 100% under ideal conditions.

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Mo, Dongmei, and Wai Keung Wong. "Fabric Defect Classification based on Deep Hashing Learning." AATCC Journal of Research 8, no. 1_suppl (2021): 191–201. http://dx.doi.org/10.14504/ajr.8.s1.23.

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Classifying categories of fabric defects can greatly help to identify the source of causing fabric defects in the textile manufacturing process. Most existing artificial intelligence based methods focus on identifying and locating defective regions and do not analyze the categories of the defects. On the other hand, as current fabric defect detection methods depend on handcrafted features, they can only handle fabric with specific patterns or textures. In this paper, we propose a novel model which can learn high-level representation from the automatic observations of the input images that can

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Li, Zhenwei, Shihai Zhang, Chongnian Qu, Zimiao Zhang, and Feng Sun. "Research on multi-defects classification detection method for solar cells based on deep learning." PLOS ONE 19, no. 6 (2024): e0304819. http://dx.doi.org/10.1371/journal.pone.0304819.

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Solar cells are playing a significant role in aerospace equipment. In view of the surface defect characteristics in the manufacturing process of solar cells, the common surface defects are divided into three categories, which include difficult-detecting defects (mismatch), general defects (bubble, glass-crack and cell-crack) and easy-detecting defects (glass-upside-down). Corresponding to different types of defects, the deep learning model with different optimization methods and a classification detection method based on multi-models fusion are proposed in the paper. In the proposed model, in

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Kumaresh, Sakthi, and R. Baskaran. "Software Defect Prevention through Orthogonal Defect Classification (ODC)." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 11, no. 3 (2013): 2393–400. http://dx.doi.org/10.24297/ijct.v11i3.1166.

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â€œQuality is never an accident; it is always the result of intelligent effortâ€ [10]. In the process of making quality software product, it is necessary to have effective defect prevention process, which will minimize the risk of making defects /errors in software deliverables. An ideal approach would involve effective software development process with an integrated defect prevention process. This paper presents a Defect Prevention Model in which Defect Prevention Process(DPP) is integrated into software development life cycle to reduce the defects at early stages itself, thereby reducing th

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Dissertations / Theses on the topic "Defects classification"

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Bengali, Umme Salma Yusuf. "Pixel classification of iris transillumination defects." Thesis, University of Iowa, 2012. https://ir.uiowa.edu/etd/3260.

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Mar, Nang Seng Siri. "Vision-based classification of solder joint defects." Thesis, Queensland University of Technology, 2010. https://eprints.qut.edu.au/37273/1/Nang_Mar_Thesis.pdf.

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Inspection of solder joints has been a critical process in the electronic manufacturing industry to reduce manufacturing cost, improve yield, and ensure product quality and reliability. The solder joint inspection problem is more challenging than many other visual inspections because of the variability in the appearance of solder joints. Although many research works and various techniques have been developed to classify defect in solder joints, these methods have complex systems of illumination for image acquisition and complicated classification algorithms. An important stage of the analysis

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Wang, Hui. "Software Defects Classification Prediction Based On Mining Software Repository." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-216554.

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An important goal during the cycle of software development is to find and fix existing defects as early as possible. This has much to do with software defects prediction and management. Nowadays,many big software development companies have their own development repository, which typically includes a version control system and a bug tracking system. This has no doubt proved useful for software defects prediction. Since the 1990s researchers have been mining software repository to get a deeper understanding of the data. As a result they have come up with some software defects prediction models

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Wilson, Duncan John. "Classification of defects using uncertainty in industrial web inspection." Thesis, University of London, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.286894.

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Balakrishnan, Harinarayanan. "FDICS : a vision-based system for identification and classification of fabric defects." Thesis, Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/8465.

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Allanqawi, Khaled Kh S. Kh. "A framework for the classification and detection of design defects and software quality assurance." Thesis, Kingston University, 2015. http://eprints.kingston.ac.uk/34534/.

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In current software development lifecyeles of heterogeneous environments, the pitfalls businesses have to face are that software defect tracking, measurements and quality assurance do not start early enough in the development process. In fact the cost of fixing a defect in a production environment is much higher than in the initial phases of the Software Development Life Cycle (SDLC) which is particularly true for Service Oriented Architecture (SOA). Thus the aim of this study is to develop a new framework for defect tracking and detection and quality estimation for early stages particularly f

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Bond, Brian Jr. "Characterization of Wood Features Using Color, Shape, and Density Parameters." Diss., Virginia Tech, 1998. http://hdl.handle.net/10919/30629.

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Automated defect detection methods allow the forest products industry to better utilize its resources by improving yield, reducing labor costs, and allowing minimum lumber grades to be utilized more intelligently. While many methods have been proposed on what sensors and processing methods should be used to detect and classify wood features, there exists a lack of understanding of what parameters are best used to differentiate wood features. The goal of this research is to demonstrate that by having an in depth knowledge of how wood features are represented by color, shape, and density param

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Niewalda, Tobias. "Deep Learning Based Classification of Rail Defects Using On-board Monitoring in the Stockholm Underground." Thesis, KTH, Spårfordon, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273576.

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The purpose of this work is to ﬁnd out if an artiﬁcial neural network can be useful purpose of this work is to ﬁnd out if an artiﬁcial neural network can be useful in order to detect rail squats with the existing Quiet Track Measurement System (QTMS). Squats are surface-initiated rail defects which arise due to rolling contact fatigue. The monitoring system, installed on seven trains running on the green line in the Stockholm underground, aims to improve the maintenance process. The early detection and surveillance of defects helps to extend the service life of the tracks and reduce operating

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Nouri, Arash. "Correlation-Based Detection and Classification of Rail Wheel Defects using Air-coupled Ultrasonic Acoustic Emissions." Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/78139.

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Defected wheel are one the major reasons endangered state of railroad vehicles safety statue, due to vehicle derailment and worsen the quality of freight and passenger transportation. Therefore, timely defect detection for monitoring and detecting the state of defects is highly critical. This thesis presents a passive non-contact acoustic structural health monitoring approach using ultrasonic acoustic emissions (UAE) to detect certain defects on different structures, as well as, classifying the type of the defect on them. The acoustic emission signals used in this study are in the ultrasonic r

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Partyka-Jankowska, Ewa, Bogdan Sepiol, Fritz Gröstlinger, et al. "Dynamic of defects in an iron monolayer on W (110)." Diffusion fundamentals 11 (2009) 51, S. 1-2, 2009. https://ul.qucosa.de/id/qucosa%3A12963.

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Books on the topic "Defects classification"

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Hayes, Samuel P. Color Defects: Measurement, Classification, Heredity. Creative Media Partners, LLC, 2021.

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Grazzi-Soncini, Giacomo. Wine: Classification, Wine Tasting, Qualities and Defects. Franklin Classics, 2018.

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Grazzi-Soncini, Giacomo. Wine: Classification, Wine Tasting, Qualities and Defects. Franklin Classics Trade Press, 2018.

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Grazzi-Soncini, Giacomo. Wine: Classification, Wine Tasting, Qualities and Defects. Franklin Classics Trade Press, 2018.

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Wine: Classification, Wine Tasting, Qualities and Defects. Franklin Classics, 2018.

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Soncini, G. Grazzi. Wine: Classification, Wine Tasting, Qualities and Defects. Creative Media Partners, LLC, 2022.

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ANSI/AAMI SW91:2018; Classification of defects in health software. AAMI, 2018. http://dx.doi.org/10.2345/9781570207075.

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Papaelias, Mayorkinos, and Fausto Pedro Garca Mrquez. Fault Detection: Classification, Techniques and Role in Industrial Systems. Nova Science Publishers, Incorporated, 2014.

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Lamari, Foudil, and Jean-Marie Saudubray. Disorders of Complex Lipids Synthesis and Remodeling. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199972135.003.0066.

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Defective lipid catabolic pathways are involved in numerous inherited metabolic diseases such as lysosomal storage diseases and peroxisome biogenesis disorders. We recently described a new classification of a rapidly growing group of inherited metabolic disorders involving biosynthesis and remodeling of complex lipids including phospholipids and sphingolipids. The remarkable progress achieved over the last decade in high throughput gene sequencing and in lipid analysis technologies have enabled the description of more than 40 diseases linked to defects in enzymes involved in these pathways. So

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Uffman, Joshua C. Neuronal Ceroid Lipofuscinoses (Batten Disease). Edited by Kirk Lalwani, Ira Todd Cohen, Ellen Y. Choi, and Vidya T. Raman. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190685157.003.0042.

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Neuronal ceroid lipofuscinoses (NCL) are a group of autosomal recessive genetic disorders which represent the most common form of childhood neurodegenerative disease. Classically the disease was described according to the age of diagnosis resulting in four common phenotypes: (i) infantile or Santavuori-Haltia, (ii) late infantile or Jansky-Bielschowsky, (iii) juvenile or Spielmeyer-Vogt, and (iv) adult or Kufs. With advances in genetic mutational analysis techniques and improved understanding of NCL disease as a whole, disease classification now focuses on which of the known genetic defects is

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Book chapters on the topic "Defects classification"

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Kumar, Sushil, Meera Sharma, S. K. Muttoo, and V. B. Singh. "Autoclassify Software Defects Using Orthogonal Defect Classification." In Computational Science and Its Applications – ICCSA 2022 Workshops. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-10548-7_23.

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Kosutic, Damir. "Classification of Perineal Defects." In Perineal Reconstruction. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-97691-0_6.

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Engh, Gerard A. "Classification of Bone Defects." In Surgical Techniques in Total Knee Arthroplasty. Springer New York, 2002. http://dx.doi.org/10.1007/0-387-21714-2_53.

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Kleman, Maurice. "The Topological Classification of Defects." In Formation and Interactions of Topological Defects. Springer US, 1995. http://dx.doi.org/10.1007/978-1-4615-1883-9_2.

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Cordeiro, Peter G. "Classification System for Mandibulectomy Defects." In Atlas of Mandibular and Maxillary Reconstruction with the Fibula Flap. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-10684-3_1.

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Cordeiro, Peter G. "Classification System for Maxillectomy Defects." In Atlas of Mandibular and Maxillary Reconstruction with the Fibula Flap. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-10684-3_2.

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Krautkrämer, Josef, and Herbert Krautkrämer. "Detection and Classification of Defects." In Ultrasonic Testing of Materials. Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-662-10680-8_20.

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Fink, Bernd. "Classification of Femoral Bone Defects." In Femoral Revision Arthroplasty. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-84821-7_3.

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Anderson, R. H., and F. J. Macartney now deceased. "Classification and Nomenclature of Congenital Heart Defects." In Surgery for Congenital Heart Defects. John Wiley & Sons, Ltd, 2006. http://dx.doi.org/10.1002/0470093188.ch1.

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Trebin, H. R. "Classification of Defects in Liquid Crystals." In Defects in Liquid Crystals: Computer Simulations, Theory and Experiments. Springer Netherlands, 2001. http://dx.doi.org/10.1007/978-94-010-0512-8_1.

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Conference papers on the topic "Defects classification"

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Qiao, Yibo, and Yining Chen. "TransNet: Automatic Classification Network for Nanoscale Wafer SEM Defects." In 2024 IEEE International Symposium on the Physical and Failure Analysis of Integrated Circuits (IPFA). IEEE, 2024. http://dx.doi.org/10.1109/ipfa61654.2024.10691180.

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Yu, Tao, Ye Xia, and Limin Sun. "A Machine Learning-Enhanced Method to Bridge Condition Evaluation considering Defect Prioritization." In IABSE Symposium, Tokyo 2025: Environmentally Friendly Technologies and Structures: Focusing on Sustainable Approaches. International Association for Bridge and Structural Engineering (IABSE), 2025. https://doi.org/10.2749/tokyo.2025.0116.

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<p>Accurate bridge condition assessment is essential for bridge management and maintenance. Traditional hierarchical evaluation methods in China have highlighted two key issues: components with minor defects are often scored lower than those with severe defects, and the defect names in inspection reports do not always align with those described in the relevant guidelines. This paper introduces a modified bridge assessment method to address these issues. The proposed methods include adjusting the scoring model to prioritize structural defects and reduce deductions for non- structural defe

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Zhao, Rongxin, Feng Wang, Huayong Wu, and Zijie Zhou. "Recognition of Apparent Defects in Bridge Cable Bundle Wraps Based on Deep Learning Algorithms." In IABSE Symposium, Tokyo 2025: Environmentally Friendly Technologies and Structures: Focusing on Sustainable Approaches. International Association for Bridge and Structural Engineering (IABSE), 2025. https://doi.org/10.2749/tokyo.2025.1992.

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<p>Cables, as the main load-bearing components, have a profound impact on the lifespan of cable- structured bridges. With the rapid development of bridge construction in China, collapses due to cable fractures occur from time to time. Traditional methods for detecting apparent defects of cable sheaths through manual inspection are labor-intensive and involve certain safety risks, failing to meet the demands of the new era for cable defects detection. This paper employs mobile detection equipment to collect and locate high-definition images of cable sheaths, constructs an in-service bridg

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Massalkhi, Houssam, Abdulla Lutfi, and Ayman El-Hag. "Classification of Defects in Outdoor Ceramic Insulators using Machine Learning." In 2024 25th International Middle East Power System Conference (MEPCON). IEEE, 2024. https://doi.org/10.1109/mepcon63025.2024.10850157.

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Nagar, Sweety, Manas Kumar Mishra, and Praveen Kumar Rai. "Using Densenet169 for Image-Based Classification of Solar Panel Defects." In 2024 7th International Conference on Contemporary Computing and Informatics (IC3I). IEEE, 2024. https://doi.org/10.1109/ic3i61595.2024.10828815.

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Arachchi, S. H. A., P. H. K. Vidushka, S. N. Niles, and R. P. Abeysooriya. "Classification of Defects of Cotton Yarns Using Convolutional Neural Networks." In 2024 9th International Conference on Information Technology Research (ICITR). IEEE, 2024. https://doi.org/10.1109/icitr64794.2024.10857711.

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Bień, Jan, and Małgorzata Gładysz-Bień. "Multi-level Classification of Bridge Defects in Asset Management." In IABSE Symposium, Guimarães 2019: Towards a Resilient Built Environment Risk and Asset Management. International Association for Bridge and Structural Engineering (IABSE), 2019. http://dx.doi.org/10.2749/guimaraes.2019.1100.

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<p>In the paper a proposal of the unified multi-level classification of bridge defects declining condition of bridges is presented as one of the most important elements of asset management. General scheme of bridge degradation process is described with classifications of basic mechanisms of bridge degradation as well as stimulators of degradation mechanisms. Criteria of defects classification are proposed taking into account effects of activities of bridge degradation mechanisms. The proposed general conception of classification methodology of bridge defects is addressed to all types of

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Wolfe, Scott, and Steve McGarvey. "Scanning electron microscope automatic defect classification of process induced defects." In SPIE Advanced Lithography, edited by Martha I. Sanchez and Vladimir A. Ukraintsev. SPIE, 2017. http://dx.doi.org/10.1117/12.2258122.

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Ma, Can, Luyang Jie, Yiming Yao, Tong Xu, and Lilei Hu. "Spatial Attention Enhanced Wafer Defect Classification Algorithm for Tiny Defects." In 2023 IEEE 15th International Conference on Advanced Infocomm Technology (ICAIT). IEEE, 2023. http://dx.doi.org/10.1109/icait59485.2023.10367417.

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Gorantiwar, Anish, Saied Taheri, Feraidoon Zahiri, and Bijan Moslehi. "Real Time Bearing Defect Classification Using Time Domain Analysis and Deep Learning Algorithms." In WCX SAE World Congress Experience. SAE International, 2023. http://dx.doi.org/10.4271/2023-01-0096.

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<div class="section abstract"><div class="htmlview paragraph">Structural Health Monitoring (SHM), especially in the field of rotary machinery diagnosis, plays a crucial role in determining the defect category as well as its intensity in a machine element. This paper proposes a new framework for real-time classification of structural defects in a roller bearing test rig using time domain-based classification algorithms. Along with the bearing defects, the effect of eccentric shaft loading has also been analyzed. The entire system comprises of three modules: sensor module – using acc

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Reports on the topic "Defects classification"

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Dr. Gabe V. Garcia. Automated Diagnosis and Classification of Steam Generator Tube Defects. Office of Scientific and Technical Information (OSTI), 2004. http://dx.doi.org/10.2172/833464.

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Ting, Wang, and Jeff Sutherland. PR-469-143708-R02 In-line Inspection and Assessment for Pipeline Girth Weld Defects. Pipeline Research Council International, Inc. (PRCI), 2018. http://dx.doi.org/10.55274/r0011487.

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During 2010 to 2012, the United States reported a total of eight girth weld failures and economic loss amounted to $4,382,000 [Summarized from data provided by PHMSA, http://www.phmsa.dot.gov/pipeline/library/data-stats/flagged-data-files]. PRCI has several projects (current and historic) that investigate various integrity concerns of vintage girth weld defects. Globally, the integrity of girth welds of oil and gas pipelines has increased as a concern due to failures with high consequences. A primary integrity issue to pipelines that has been the motivation of this project, considers defects o

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Zhao, George, Grang Mei, Bulent Ayhan, Chiman Kwan, and Venu Varma. DTRS57-04-C-10053 Wave Electromagnetic Acoustic Transducer for ILI of Pipelines. Pipeline Research Council International, Inc. (PRCI), 2005. http://dx.doi.org/10.55274/r0012049.

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In this project, Intelligent Automation, Incorporated (IAI) and Oak Ridge National Lab (ORNL) propose a novel and integrated approach to inspect the mechanical dents and metal loss in pipelines. It combines the state-of-the-art SH wave Electromagnetic Acoustic Transducer (EMAT) technique, through detailed numerical modeling, data collection instrumentation, and advanced signal processing and pattern classifications, to detect and characterize mechanical defects in the underground pipeline transportation infrastructures. The technique has four components: (1) thorough guided wave modal analysis

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Gabe V. Garcia. Eddy Current Signature Classification of Steam Generator Tube Defects Using A Learning Vector Quantization Neural Network. Office of Scientific and Technical Information (OSTI), 2005. http://dx.doi.org/10.2172/836575.

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Heifetz, Alexander, Victoria Ankel, Dmitry Shribak, and Wei-Ying Chen. Performance of Pulsed Thermal Tomography Imaging with Machine Learning-Based Classification of Defects in Additively Manufactured Structures. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1823035.

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Nieland and Ying. L52105 Improvement in Performance in the Mark III Elastic Wave. Pipeline Research Council International, Inc. (PRCI), 2003. http://dx.doi.org/10.55274/r0011087.

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The Elastic Wave (EW) technology has a proven record of detecting longitudinal cracking in gas and liquid pipelines. However, the historical dig success rate for this inspection tool is only 1 in 4; i.e. for every four excavations carried out by pipeline operators, following an EW inspection, typically a crack or crack field will only be found at one of those excavations. This project set out to: Understand the ultrasonic data available to the inspection tool, establish whether there is information in the raw signal to differentiate between cracks and non-cracks, develop potential crack discri

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Delwiche, Michael, Yael Edan, and Yoav Sarig. An Inspection System for Sorting Fruit with Machine Vision. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7612831.bard.

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Concepts for real-time grading of fruits and vegetables were developed, including multi-spectral imaging with structured illumination to detect and distinguish surface defects from concavities. Based on these concepts, a single-lane conveyor and inspection system were designed and evaluated. Image processing algorithms were developed to inspect and grade large quasi-spherical fruits (peaches and apples) and smaller dried fruits (dates). Adjusting defect pixel thresholds to achieve a 25% error rate on good apples, classification errors for bruise, crack, and cut classes were 51%, 42%, and 46%,

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Engel, Bernard, Yael Edan, James Simon, Hanoch Pasternak, and Shimon Edelman. Neural Networks for Quality Sorting of Agricultural Produce. United States Department of Agriculture, 1996. http://dx.doi.org/10.32747/1996.7613033.bard.

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The objectives of this project were to develop procedures and models, based on neural networks, for quality sorting of agricultural produce. Two research teams, one in Purdue University and the other in Israel, coordinated their research efforts on different aspects of each objective utilizing both melons and tomatoes as case studies. At Purdue: An expert system was developed to measure variances in human grading. Data were acquired from eight sensors: vision, two firmness sensors (destructive and nondestructive), chlorophyll from fluorescence, color sensor, electronic sniffer for odor detecti

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Gleason, S., and A. Kulkarni. Semiconductor yield improvements through automatic defect classification. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/508162.

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Gleason, S. S., M. A. Hunt, H. Sari-Sarraf, and A. Kulkarni. Semiconductor Yield Improvement Through Automatic Defect Classification. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/770402.

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