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169 articles for “accuracy parameter”
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Research ArticleOpen accessIn the abstractAn Enhanced Algorithm for Small Object Detection based on Thermal Imaging Using YOLOv8-EPBRavina Gupta, Sarika Jain, Manoj KumarObject detection is one of the most important and challenging problems in the computer vision domain. Using the power of deep models, researchers have carefully explored and made significant contributions to increasing the effectiveness of object detection and related tasks, such as object identification, localization, and segmentation. This progress is due to the rapid progress of deep learning in the … …Journal of Computer Science, Vol. 21, Issue 6 · 13 Jun 2025 · 4,212 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Prediction Model for Predictive Maintenance Based on K-Nearest Neighbor Method for Air Navigation Equipment FacilitiesRachmat Hidayat, Ditdit Nugeraha UtamaThe aging of air navigation facilities leads to a decline in equipment performance and reliability, posing significant challenges for aviation organizations in the large-scale replacement of outdated systems, as well as in managing budgets and resources. To address these issues, a performance prediction model for equipment was developed using the K-Nearest Neighbor (KNN) method, aimed at enhancing maintenance planning and … …Journal of Computer Science, Vol. 21, Issue 4 · 4 Mar 2025 · 5,653 accessesView PDFCite
Research ArticleOpen accessIn the abstractPolymer Processing and Performance Testing Based on Kruskal Algorithm for Numerical AnalysisYan TangPolymer processing is an injection molding product widely used in communication, medical, and other fields. The processing and forming of polymers involve complex processes, including many parameter controls to ensure the quality of finished products. This study innovatively uses the Kruskal algorithm to conduct numerical analysis on the performance of polymer processing and molding to obtain a scientifically efficient parameter … …American Journal of Biochemistry and Biotechnology, Vol. 20, Issue 3 · 29 Jul 2024 · 4,270 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Distillation GAN Model for Network Intrusion DetectionChandrakala C B, Sai Sreevall, Raghudathesh G PThis study presents a distillation-based Generative Adversarial Network (GAN) model designed for intrusion detection in network systems. A Teacher-Student architecture is proposed, in which a single teacher generator is utilized to train both the teacher discriminator and the student discriminator. The model was trained to identify anomalies present in network traffic intrusions by tuning the min-max loss function in GANs. … …Journal of Computer Science, Vol. 22, Issue 2 · 5 Mar 2026 · 1,549 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhancing Dam Safety and Management: Long Short-Term Memory Based Predictive Models for Accurate Alert ForecastingNisha C. M, N. ThangarasuDam management and early alert systems are critical for effective water resource management. Accurate prediction of dam alert signals facilitates proactive decision-making, thereby aiding in the effective management and reduction of potential risks linked to dam operations. Within this research, Long Short-Term Memory (LSTM) networks are utilized to forecast dam alert signals issued from the dam by leveraging daily parameters, … …Journal of Computer Science, Vol. 22, Issue 1 · 6 Feb 2026 · 1,626 accessesView PDFCite
Research ArticleOpen accessIn the abstractEscalating SVM-Efficiency by Sequential QP LP and Slack Variable AnalysisAmit Kumar Kundu, Rezaul Karim, Ali Ahmed AveSupport Vector Machine (SVM) is a highly attractive algorithm among many machine learning models due to its generalization power and classification performance based on sound mathematical formulation being convex that offers global minimum. However, despite being sparse, its high classification cost from kernel execution with Support Vectors (SVs) reduces the user's interest when there are hard computational constraints in the … …Journal of Computer Science, Vol. 19, Issue 10 · 6 Sep 2023 · 5,913 accessesView PDFCite
Research ArticleOpen accessIn the abstractPerformance Evaluation of Machine Learning-Based Algorithms to Predict the Early Childhood Development Among Under Five Children in BangladeshMd. Ismail Hossain, Iqramul Haq, Ashis Talukder et al.In this research, an effort has been made to apply a number of classifiers to predict Early Child Development (ECD) in the context of Bangladesh using the Bangladesh multiple indicator cluster survey, 2019 data set (i.e., to evaluate which sort of algorithm best identifies ECDI). To predict the ECD, nine well-known machine learning algorithms were applied, including Linear Regression (LR), … …Journal of Computer Science, Vol. 19, Issue 5 · 5 May 2023 · 6,838 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Backward Regressed Capsule Neural Network for Plant Leaf Disease DetectionJennifer Jepkoech, Benson Kipkemboi Kenduiywo, David Muchangi Mugo, Edna Chebet ToolThis study investigated the introduction ofbackward regression coupled with DenseNet features in a Capsule Neural Network(CapsNet) for plant leaf disease classification. Plant diseases are consideredone of the main factors influencing food production and therefore fast cropdisease detection and recognition are important in enhancing food securityinterventions. CapsNets have successfully been adopted for plant leaf diseaseclassification however, backpropagation of signals to preceding … …Journal of Computer Science, Vol. 18, Issue 9 · 8 Sep 2022 · 5,718 accessesView PDFCite
Research ArticleOpen accessIn the abstractMANAT: A Filtering-Based Method for Denoising Nonuniform Photogrammetric Point CloudsYun Sin Chong, Hui Hui Wang, Yin Chai WangThree-dimensional point clouds reconstructed from photogrammetry often exhibit noise and non-uniform sampling density, which challenges existing denoising methods that rely on precise normal estimation or extensive parameter tuning. This study presents the Multi Attribute Neighbour Attraction Technique (MANAT), a novel single-stage, density-adaptive filtering method that jointly leverages spatial position, surface normals, and color as inherent photogrammetric attributes for unified noise … …Journal of Computer Science, Vol. 22, Issue 4 · 28 Apr 2026 · 1,524 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Robust Ensemble Convolutional Neural Networks for Diagnosing Chest DiseasesMansour Ali Alhlalat, Ahmad Abdel-Aziz Sharieh, Mohammed Belal Al-ZoubiRadiologists employ X-ray images to differentiate various chest diseases. Given the intricate and meticulous nature of this diagnostic procedure, the assistance of automated models becomes imperative in detecting and diagnosing diseases from X-ray images. This research paper proposed a novel approach called Ensemble Convolutional Neural Network for Diagnosing Chest Diseases (ECDCNet), aimed at accurately and efficiently diagnosing fifteen different chest … …Journal of Computer Science, Vol. 19, Issue 12 · 27 Oct 2023 · 5,104 accessesView PDFCite