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61 results for “Feature Optimization”
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Research ArticleOpen accessIn the abstractAn Optimal Approach for Medical Image AnalysisJ. Umamaheswari, G. RadhamaniProblem statement: Image segmentation is the process that subdivides an image into its constituent parts and extracts the objects. It is one of the most critical tasks in automatic image analysis because the subdivided results will affect all the subsequent processes of image analysis, such as object representation and description, feature measurement and even the following higher level tasks such … …Current Research in Bioinformatics, Vol. 1, Issue 1 · 6 Jun 2012 · 9,513 accessesView PDFCite
Research ArticleOpen accessIn the abstractWavelet Analysis and Orthogonal Moments based Classification of Microcalcification in Digital MammogramsN. V.S. Sree Rathna Lakshmi, C. ManoharanProblem statement: An important early sign of breast cancer is the clusters of micro calcifications in digital mammograms. To assist radiologists in the diagnosis of mammographic clusters a novel hybrid algorithm has been developed. Approach: A method, for detecting micro calcification in mammograms based on combined feature set with Ant Colony Optimization (ACO) was proposed. The diagonal matrix ‘S’ obtained … …Journal of Computer Science, Vol. 7, Issue 10 · 6 Aug 2011 · 6,558 accessesView PDFCite
Research ArticleOpen accessIn the abstractPredicting Missing Attribute Values Using k-Means ClusteringNambiraj Suguna, Keppana Gowder ThanushkodiProblem statement: Predicting the value for missing attributes is an important data preprocessing problem in data mining and knowledge discovery tasks. Several methods have been proposed to treat missing data and the one used more frequently is deleting instances containing at least one missing value of a feature. When the dataset has minimum number of missing attribute values then we … …Journal of Computer Science, Vol. 7, Issue 2 · 25 Feb 2011 · 7,873 accessesView PDFCite
Research ArticleOpen accessIn the abstractMemoryless Modified Symmetric Rank-One Method for Large-Scale Unconstrained OptimizationFarzin Modarres, Malik Abu Hassan, Wah June LeongProblem statement: Memoryless QN methods have been regarded effective techniques for solving large-scale problems that can be considered as one step limited memory QN methods. In this study, we present a scaled memoryless modified Symmetric Rank-One (SR1) algorithm and investigate the numerical performance of the proposed algorithm for solving large-scale unconstrained optimization problems. Approach: The basic idea is to apply … …American Journal of Applied Sciences, Vol. 6, Issue 12 · 31 Dec 2009 · 7,981 accessesView PDFCite
Research ArticleOpen accessIn the abstractGene Selection and Classification in Microarray Datasets using a Hybrid Approach of PCC-BPSO/GA with Multi ClassifiersShilan S. Hameed, Fahmi F. Muhammad, Rohayanti Hassan, Faisal SaeedIn this study, a three-phase hybrid approach is proposed for the selection and classification of high dimensional microarray data. The method uses Pearson’s Correlation Coefficient (PCC) in combination with Binary Particle Swarm Optimization (BPSO) or Genetic Algorithm (GA) along with various classifiers, thereby forming a PCC-BPSO/GA-multi classifiers approach. As such, five various classifiers are employed in the final stage of … …Journal of Computer Science, Vol. 14, Issue 6 · 26 Jun 2018 · 9,355 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn EBA-Web based Application for Banking Information SystemKhaldoun Mohammad BatihaIn the current wake of growing technology and modernization the biggest challenge remains the optimization of our time, particularly for the business executives. For the executives the vital information at their fingertips plays an important role. In the computer era, there are many financial institutions like wise banks which provide web-based application to access all their functionalities associated with particular … …Journal of Computer Science, Vol. 2, Issue 12 · 31 Dec 2006 · 6,835 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordDeep Learning-Based Approach for Identification of Potato Leaf Diseases Using Wrapper Feature Selection and Feature ConcatenationMuhammad Ahtsam Naeem, Muhammad Asim Saleem, Jarrar Amjad et al.The potato is a widely grown crop in many regions of the world. In recent decades, potato farming has gained incredible traction in the world. Potatoes are susceptible to several illnesses that stunt their development. This plant seems to have significant leaf disease. Early Blight and Late Blight are two prevalent leaf diseases that affect potato plants. The early detection … …Journal of Computer Science, Vol. 21, Issue 5 · 12 May 2025 · 5,171 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordStudy and Analysis of Prediction Model for Heart Disease Data Using Machine Learning TechniquesB. Santhi, K. RenukaHeart disease is the number one cause of death for all communities of individuals in advanced countries and a major problem for emerging nations too. Doctors’ availability to care for the general population could not catch up with the present demand for healthcare. So, there is a severe need for a support system to assist save individuals. With novel ML … …Journal of Computer Science, Vol. 16, Issue 3 · 26 Mar 2020 · 7,784 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordCorrelating and Modeling of Extracted Features from PVT Images of Composites using Optical Flow Technique and Weight Elimination Algorithm Optimization [OFT-WEA]Mahmoud Zaki IskandaraniA new approach to the use and implementation of Optical Flow technique is presented. The technique extracts features from presented images as a function of reference image and produces percentage of matching between the reference and tested images. The new approach in using Optical Flow lies in replacing the motion part of the algorithm with differential time related changes in … …Journal of Computer Science, Vol. 13, Issue 9 · 29 Sep 2017 · 7,320 accessesView PDFCite
Research ArticleOpen accessAll words, across the recordAn Independent Rough Set Approach Hybrid with Artificial Bee Colony Algorithm for Dimensionality ReductionNambiraj Suguna, Keppana Gowder ThanushkodiProblem statement: Dimensionality reduction is viewed as an important pre-processing step for pattern recognition and data mining. As the classical rough set model considers the entire attribute set as a whole to find the subset, comparing all possible combinations of sets of attributes is difficult. Approach: In this study, we have introduced an improved Rough Set-based Attribute Reduction (RSAR) namely … …American Journal of Applied Sciences, Vol. 8, Issue 3 · 25 Mar 2011 · 8,334 accessesView PDFCite