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374 results for “classification accuracy”
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Research ArticleOpen accessPhrase in the titleImage Pre-Processing Techniques to Improve DBT Classification Accuracy With CNN ResNet-50Qodri Aziz, Slamet Riyadi et al.Digital Breast Tomosynthesis (DBT) is a three-dimensional imaging technology that is meant to determine breast cancer more accurately than regular mammograms. But low contrast and noise can make DBT images less clear, which can make deep learning-based classification less accurate. This study seeks to assess the impact of diverse preprocessing techniques on breast cancer classification outcomes utilizing the ResNet-50 Convolutional … …Journal of Computer Science, Vol. 22, Issue 10 · 21 Oct 2026 · 349 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleMulti-Temporal Sentinel-2 Images for Classification AccuracyYuhendra, Eva YuliantiThe term ‘multi-temporal’ refers to data recorded by sensors scanning the same scene at different dates and times. In this research, Sentinel-2A images were selected for the analyses. Sentinel-2 is a very new program of the European Space Agency (ESA) designed for fine spatial resolution global monitoring. Land Cover–Land Use (LCLU) classification tasks can take advantage of the fusion of … …Journal of Computer Science, Vol. 15, Issue 2 · 22 Feb 2019 · 7,953 accessesView PDFCite
Review ArticleOpen accessEvery word in the titleImproving 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 PDFCite
Research ArticleOpen accessEvery word in the titleDetermination of SVM-RBF Kernel Space Parameter to Optimize Accuracy Value of Indonesian Batik Images ClassificationAvinanta Tarigan, Dewi Agushinta, Adang Suhendra, Fikri BudimanImage retrieval using Support Vector Machine (SVM) classification verydepends on kernel function and parameter. Kernel function used by dot productsubstitution from old dimension feature to new dimension depends on imagedataset condition. In this research, parameter of Gaussian /Radial BasisFunction (RBF) kernel function is optimized using multi class non-linear SVMmethod and implemented to training and test datasets of traditional Indonesian batik … …Journal of Computer Science, Vol. 13, Issue 11 · 23 Oct 2017 · 7,530 accessesView PDFCite
Research ArticleOpen accessEvery word in the titleA New Method for Accuracy Assessment of Sub-Pixel Classification ResultsH. Emami, B. MojaradiProblem statement: Classification accuracy assessment is the main stage of information extraction to evaluate the performance of a classifier. According to the output's classifiers (thematic map/fraction map), a properly strategy for accuracy assessment should be taken into consideration. Since pure pixels are used in traditional accuracy assessment of full pixel classifiers they are not suitable for assessment of sub-pixel classifiers. … …American Journal of Engineering and Applied Sciences, Vol. 2, Issue 2 · 30 Jun 2009 · 7,475 accessesView PDFCite
Research ArticleOpen accessIn the keywordsLAND USE LAND COVER DYNAMICS OF NILGIRIS DISTRICT, INDIA INFERRED FROM SATELLITE IMAGERIESP. Nalina, T. Meenambal, R. Sathyanarayan SridharLand use Land cover changes are critical components in managing natural resources especially in hilly region as they trigger the erosion of soil and thus making the zone highly vulnerable to landslides. The Nilgiris district of Tamilnadu state in India is the first biosphere in Western Ghats region with rare species of flora and fauna and often suffered by frequent … …American Journal of Applied Sciences, Vol. 11, Issue 3 · 13 Jan 2014 · 7,857 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Gene Selection Algorithm using Bayesian Classification ApproachAlok Sharma, Kuldip K. PaliwalIn this study, we propose a new feature (or gene) selection algorithm using Bayes classification approach. The algorithm can find gene subset crucial for cancer classification problem. Problem statement: Gene identification plays important role in human cancer classification problem. Several feature selection algorithms have been proposed for analyzing and understanding influential genes using gene expression profiles. Approach: The feature selection … …American Journal of Applied Sciences, Vol. 9, Issue 1 · 24 Nov 2011 · 8,307 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA New Approach Using Data Envelopment Analysis for Ranking Classification AlgorithmsA. Bazleh, P. Gholami, F. SoleymaniProblem statement: A variety of methods and algorithms for classification problems have been developed recently. But the main question is that how to select an appropriate and effective classification algorithm. This has always been an important and difficult issue. Approach: Since the classification algorithm selection task needs to examine more than one criterion such as accuracy and computational time, it … …Journal of Mathematics and Statistics, Vol. 7, Issue 4 · 15 Sep 2011 · 7,443 accessesView PDFCite
Research ArticleOpen accessIn the keywordsAn 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
Research ArticleOpen accessIn the keywordsPattern Classification: An Improvement Using Combination of VQ and PCA Based TechniquesAlok Sharma, Kuldip K. Paliwal, Godfrey C. OnwuboluThis study firstly presents a survey on basic classifiers namely Minimum Distance Classifier (MDC), Vector Quantization (VQ), Principal Component Analysis (PCA), Nearest Neighbor (NN) and K-Nearest Neighbor (KNN). Then Vector Quantized Principal Component Analysis (VQPCA) which is generally used for representation purposes is considered for performing classification tasks. Some classifiers achieve high classification accuracy but their data storage requirement and … …American Journal of Applied Sciences, Vol. 2, Issue 10 · 31 Oct 2005 · 6,498 accessesView PDFCite