62 articles for “Global Feature”

Research ArticleOpen accessPhrase in the titleA Multimodal Biometric System using Global Features for Identical Twins IdentificationBayan Omar Mohammed, Siti Mariyam ShamsuddinPattern recognition studies are currently focusing on twin’s biometric identification. The system of twins’ biometric Identification can potentially differentiate the individual’s biometric pattern. With the new Unimodal biometric identification, identical twins are precisely and reliably identified, with well exposure of certain traits. However, it is much more challenging to identify identical twins as they share so many similarities between them, … …Journal of Computer Science, Vol. 14, Issue 1 · 18 Jan 2018 · 8,014 accessesView PDF Cite

Research ArticleOpen accessPhrase in the titleFINGER KNUCKLE-PRINT IDENTIFICATION BASED ON LOCAL AND GLOBAL FEATURE EXTRACTION USING SDOSTN. B. Mahesh Kumar, K. PremalathaFinger knuckle-print biometric system has widely used in modern e-world. The region of interest is needed as the key for the feature extraction in a good biometric system. The symmetric discrete orthonormal stockwell transform provides the computational efficiency and multi-scale information of wavelet transforms, while providing texture features in terms of Fourier frequencies. It outperforms leading wavelet-based texture analysis methods. … …American Journal of Applied Sciences, Vol. 11, Issue 6 · 3 Apr 2014 · 6,927 accessesView PDF Cite

Research ArticleOpen accessPhrase in the title3D Object Recognition using Multiclass Support Vector Machine-K-Nearest Neighbor Supported by Local and Global FeatureC. Chandrasekar, R. MuralidharanProblem statement: In this study, a new method has been proposed for the recognition of 3D objects based on the various views of the object. The proposed method is evolved from the two promising methods available for object recognition. Approach: The proposed method uses both the local and global features extracted from the images. For feature extraction, Hu’s Moment invariant … …Journal of Computer Science, Vol. 8, Issue 8 · 4 Aug 2012 · 7,285 accessesView PDF Cite

Research ArticleOpen accessIn the keywordsEnhancing Semantic Web Retrieval Through Ontology-Driven Feature Extraction: A Novel PropositionMeer Hazar Khan, Muhammad Imran Sharif, Mehwish Mehmood et al.Web images represent unstructured data sets which often lead to challenges when users try to locate distinct images via text-based searches on the web. Such difficulties stem from different factors, e.g., redundant image storage, irrelevant metadata tags, and incorrect associations. To overcome this issue, we propose a semantic model based on the ontology language that enables users to find images … …Journal of Computer Science, Vol. 20, Issue 5 · 23 Feb 2024 · 5,562 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEW-GAT: Edge-Weighted Graph Attention Framework for Patient-Aware Heart Disease Classification Using Feature-to-Feature Similarity GraphsRamakrishna Reddy Badveli, Nijaguna Gollara Siddappa, Sundeep Kumar KanipakapatnamHeart disease remains an important cause of global death, requiring accurate and clinically interpretable prediction models. However, traditional Machine Learning (ML) methods often fail to capture meaningful dependencies among clinical features and lack robustness across diverse patient populations. To overcome these issues, this research introduces an Edge-Weighted Graph Attention Network (EW-GAT) for patient-aware heart disease classification. The approach first models … …Journal of Computer Science, Vol. 22, Issue 7 · 25 Jul 2026 · 912 accessesView PDF Cite

Review ArticleOpen accessIn the abstractImproving Classification and Clustering Accuracy of Palembang Duku Fruit Quality via CNN-K-Means IntegrationHenny Hartono, Francka Sakti Lee, Herlina Herlina et al.Duku Palembang (Lansium domesticum Corr.) is a leading commodity from South Sumatra with high economic value. The quality assessment process for duku has traditionally relied on manual visual inspection, which is subjective, time-consuming, and inconsistent, especially at large production scales. This study proposes an integrative framework combining Convolutional Neural Network (CNN) and K-Means Clustering to improve the accuracy of classification … …OnLine Journal of Biological Sciences, Vol. 26, Issue 2 · 8 May 2026 · 1,475 accessesView PDF Cite

Research ArticleOpen accessIn the abstractDeep Learning Approaches for Early Detection of Skin Cancer Disease Detection Using Segmentation and Classification with Severity AnalysisPunam R. Patil, Ritu TandonThe utmost prevalent type of the disease, skin cancer claims millions of lives every year, poses a serious public health threat particularly melanoma, which is often fatal if not detected early. Early diagnosis is crucial, yet traditional methods frequently fall short due to image quality limitations and the complexity of visual differentiation. With an emphasis on severity analysis, this study … …Journal of Computer Science, Vol. 21, Issue 9 · 24 Nov 2025 · 2,051 accessesView PDF Cite

Research ArticleOpen accessIn the abstractHybrid SIFT-DCT Approach for Face Matching of BuddhaStatues: Addressing Negative Similarity Metrics with SHashingLinda Marlinda, Fikri Budiman et al.Art and cultural heritage rely on image processing techniques forpreservation and analysis. A key challenge in this study is accuratelydetecting highly similar Buddha faces despite variations in lighting, rotation,and minor facial differences. This paper proposes a Content-Based ImageRetrieval (CBIR) framework that integrates Discrete Cosine Transform(DCT) and Scale-Invariant Feature Transform (SIFT) to enhance face-matching accuracy. The system is tested on a … …Journal of Computer Science, Vol. 21, Issue 7 · 29 Jul 2025 · 3,483 accessesView PDF Cite

Research ArticleOpen accessIn the abstractComparative Analysis on Prediction of Chronic KidneyDisease by various Machine Learning ModelsNikhil Verma, Tripti Sharma, Bobbinpreet Kaur, Ayush DograChronic Kidney Disease (CKD) is a prevalent global healthconcern, which is affecting a number of people in the whole world. Earlydetection & precise checking of CKD are really important for essentialsupervision & intervention to prevent disease progression and associatedcomplications. Machine learning (ML) models have emerged as favourabletools for CKD detection due to their ability to analyse complex data patternsand provide … …Journal of Computer Science, Vol. 21, Issue 6 · 24 May 2025 · 5,939 accessesView PDF Cite

Research ArticleOpen accessIn the abstractAn Adaptive Data Preprocessing Framework for Improved Learning: A Case Study of Tangier Container TerminalMostafa Al Uahabi, Hicham Attariuas, Mohammed Saleh, Mohamed ChentoufContainer terminals are critical nodes within the maritime transportation system that have a vital function in global merchandise trade, handling a significant volume of cargo through the use of various equipment and personnel. Thus, the efficiency of container terminal operations relies heavily on the ability to collect, analyze, and utilize operational data. However, such data can be corrupted by noise, … …Journal of Computer Science, Vol. 20, Issue 3 · 25 Jan 2024 · 5,585 accessesView PDF Cite