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157 articles for “Defect”
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Research ArticleOpen accessEvery word in the titleLightweight Deep Learning Model for TFT-LCD Pixel Defect Detection Using MobileNetV2J. Sheikshabjan, K. Dhanakodi, A.T. Rajamanickam et al.The proposed methodology aims to achieve high classification accuracy while maintaining computational efficiency and minimizing inference latency, making it highly suitable for real-time industrial inspection scenarios. This study evaluated five traditional transfer learning models (VGG16, ResNet50, MobileNetV2, Xception, and InceptionV3) for comparison in pixel defect detection. MobileNetV2-based implementation demonstrated a competitive average test accuracy of 0.9916, outperforming several baselines while … …Journal of Computer Science, Vol. 22, Issue 8 · 8 Sep 2026 · 673 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleUncertainty-Aware Ensemble Models for Improved Defect Detection in Noisy DataMadhavi Perla, Gadi Lava Raju, A Radha Krishna et al.Software defect prediction plays a crucial role in ensuring software quality and reliability, especially as modern systems become more complex and data rich. This study introduces an uncertainty-aware ensemble learning framework aimed at improving defect classification performance in noisy and imbalanced datasets, particularly those from the PROMISE and NASA KC1 repositories. The proposed model integrates multiple classifiers in a multi-learner … …Journal of Computer Science, Vol. 22, Issue 4 · 27 Apr 2026 · 1,542 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleDefect Classification of Reinforced Concrete Structures with Nondestructive Tests Using Statistical and Machine Learning MethodsSajjad Sayyar-Roudsari, Armaghan Shalbaftabar, Farshid Damirchilo et al.In this study, twelve reinforced concrete beams were constructed, each with specified dimensions and initial compressive strength. The beams were divided into four groups: A control group without any defect, a void group featuring a centrally located void, a corrosion group and a debonding group. The impact echo test was used for nondestructive testing, gathering data on compressive and shear … …American Journal of Engineering and Applied Sciences, Vol. 17, Issue 3 · 11 Jun 2024 · 5,258 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleCapsule Defect Detection and Classification Using Enhanced MobileNet ModelWenqing Bian, Yongzhi Huang, Baolian Shan, Yanting ChangThe quality of capsules has a direct impact on human health. However, defects inevitably arise during the capsule manufacturing process, and manual sorting is required. Most studies on capsule defects focus on detecting surface imperfections and those on internal capsule defects remain relatively limited. This study classifies four types of capsules using the deep learning model MobileNet, aiming to accurately … …American Journal of Biochemistry and Biotechnology, Vol. 20, Issue 4 · 5 Nov 2024 · 5,203 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleA Systematic Literature Review of Software Defect Prediction Using Deep LearningAhmed Bahaa, Enas Mohamed Fathy, Ahmed Sharaf Eldin et al.The approaches associated with software defect prediction are used to reduce the time and cost of discovering software defects in source code and to improve the software quality in the organizations. There are two approaches to reveal the software defects in the source code. The first approach is concentrated on the traditional features such as lines of code, code complexity, … …Journal of Computer Science, Vol. 17, Issue 5 · 22 May 2021 · 10,967 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleDefect Types and Software Inspection Techniques: A Systematic Mapping StudyEdson OliveiraJr, Ricardo Theis GeraldiSoftware inspection has been used to guarantee and control the quality of products by detecting defects, which can be spread out throughout the entire software life cycle. Therefore, the main premise is to identify and reduce the number of defect types in software artifacts during inspections. This work focuses on providing an up to dated overview of existing defects in … …Journal of Computer Science, Vol. 13, Issue 10 · 13 Oct 2017 · 7,925 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleSimulations on Single Vacancy Defect Transients for Face-Center-Cubic StructureKwuanchanok Chansawang, Sunchai NilsuwankositThe simulations on single vacancy defect transients for FCC structure were conducted to study the change in its final structure, especially the average atomic volume. The numerical code &#34ALINE&#34 was employed for this purpose. The results obtained showed that when a single vacancy defect occurred in a perfect FCC-crystal structure, the average atomic volume was found to be suddenly increased … …Current Research in Biostatistics, Vol. 3, Issue 1 · 4 Sep 2013 · 6,675 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleMachine Learning Approach for Defects Identification in Dissimilar Friction Stir Welded Aluminium Alloys AA 7075-AA 1100 JointsAkshansh MishraMachine learning approaches are now applied in various manufacturing industries. Various machine learning algorithms can be implemented for prediction of the particular mechanical properties like Ultimate Tensile Strength (UTS), Elongation percentage and fracture strength of the given mechanical component and also image processing algorithms can be applied for defects detection in the mechanical components. In our recent work, we have … …Journal of Aircraft and Spacecraft Technology, Vol. 4, Issue 1 · 1 Jul 2020 · 6,701 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleComparison Between Selective Sampling and Random Undersampling for Classification of Customer Defection Using Support Vector MachineHeri Kuswanto, Yogi Sarumaha, Hayato OhwadaQuality of a product determines the customer loyalty and it can be measured by conducting a survey. Company ‘X’ that sells three kinds of product (low, medium and high price) collected very large dataset through an online survey and recorded customer defection and their characteristic. The measured variables are Update Accumulation, Product Price, Customer Type, Delivery Status and Customer Defection. … …Journal of Computer Science, Vol. 13, Issue 8 · 16 Aug 2017 · 7,263 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleHIDDEN MARKOV MODELS WITH COVARIATES FOR ANALYSIS OF DEFECTIVE INDUSTRIAL MACHINE PARTSPornpit Sirima, Premysl PokornyMonthly counts of industrial machine part errors are modeled using a two-state Hidden Markov Model (HMM) in order to describe the effect of machine part error correction and the amount of time spent on the error correction on the likelihood of the machine part to be in a &#34defective&#34 or &#34non-defective&#34 state. The number of machine parts errors were collected … …Journal of Mathematics and Statistics, Vol. 10, Issue 3 · 26 Jul 2014 · 6,859 accessesView PDFCite