6 results for “Refined Database”

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Research ArticleOpen accessIn the keywordsEfficient Approach to Discover Interval-Based Sequential PatternsR. Sadasivam, K. DuraiswamyIn most of the sequential pattern mining methodology they have concentrated only on time point base event data. But some research efforts have detailed the mining patterns from time interval based event data. In many application most of the events are occurred at time interval based event not a point based interval for example patient affected by the certain time … …Journal of Computer Science, Vol. 9, Issue 2 · 11 Apr 2013 · 6,368 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 abstractPredicting Antigenic Peptides Using a Multi-Level Transformer Model with Enhanced Feature SelectionAshwini S., Minu R. I., Jeevan KumarThis Antigenic Peptide (APs) prediction is one of the most important roles to improve vaccine design and interpret immune responses. This paper develops a Multi-Level Pooling-based Transformer model, which improves the accuracy and efficiency of predicting T-cell epitopes. The model utilizes peptide sequences from the Immune Epitope Database, employing a refined Kolaskar and Tongaonkar algorithm for feature extraction and a … …Journal of Computer Science, Vol. 21, Issue 7 · 17 Jul 2025 · 3,443 accessesView PDF Cite

Research ArticleOpen accessIn the abstractBRAIN TUMOR CLASSIFICATION BASED ON CLUSTERED DISCRETE COSINE TRANSFORM IN COMPRESSED DOMAINV. Anitha, S. MurugavalliThis study presents a novel method to classify the brain tumors by means of efficient and integrated methods so as to increase the classification accuracy. In conventional systems, the problem being the same to extract the feature sets from the database and classify tumors based on the features sets. The main idea in plethora of earlier researches related to any … …Journal of Computer Science, Vol. 10, Issue 10 · 6 May 2014 · 7,532 accessesView PDF Cite

Research ArticleOpen accessIn the abstractA Fuzzy Fast Classification for Share Market Database with Lower and Upper BoundsSrinivasan Vaiyapuri, Rajenderan Govind, Vandar Kuzhali JaganathanIn recent years, many researchers focused on the research topic of constructing fuzzy classification system. This study introduces a Fuzzy Fast Classification (FFC) approach for large data sets. It has three phases, in the first phase the large data base is reduced with the entropy by removing the number of attribute. In the second phase an approximate classification is obtained … …American Journal of Applied Sciences, Vol. 9, Issue 12 · 8 Nov 2012 · 6,669 accessesView PDF Cite

Research ArticleOpen accessIn the abstractRange Image Segmentation by Randomized Region Growing and Bayesian Edge RegularizationSmaine Mazouzi, Mohamed BatoucheWe presented and evaluated a new Bayesian method for range image segmentation. The method proceeds in to stages. First, an initial segmentation was produced by a randomized region growing technique. The produced segmentation was considered as a degraded version of the ideal segmentation, which should be then refined. In the second stage, image pixels not labeled in the first stage … …Journal of Computer Science, Vol. 3, Issue 5 · 31 May 2007 · 6,924 accessesView PDF Cite