Search Results - (( variable visualization using algorithm ) OR ( _ classification using algorithm ))
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Extremal region detection and selection with fuzzy encoding for food recognition
Published 2019“…The first algorithm locates interest points in food images using an MSER. …”
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Survival versus non-survival prediction after acute coronary syndrome in Malaysian population using machine learning technique / Nanyonga Aziida
Published 2019“…Prediction, identification, understanding and visualization of relationship between factors affecting mortality in ACS patients using feature selection and ML algorithms. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms
Published 2024“…The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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Classification of students' performance in computer programming course according to learning style
Published 2024Conference Paper -
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization
Published 2021“…Hybrid combinations of feature selection, classification and visualisation using machine learning (ML) methods have the potential for enhanced understanding and 30-day mortality prediction of patients with cardiovascular disease using population-specific data. …”
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HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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Final Year Project -
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Classification of Students' Performance in Computer Programming Course According to Learning Style
Published 2024“…The critical point of this study is the use of classification algorithm to extract patterns which are examined from the cognitive factor specific learning style. …”
Proceedings Paper -
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Decision tree as knowledge management tool in image classification
Published 2008“…Expert System has been grown so fast as a science that study how to make computer capable of solving problems that typically can only be solved by expert.It has been realized that the biggest challenge of developing expert system is the process include expert’s knowledge into the system.This research tries to model expert’s knowledge management using case based reasoning method.The knowledge itself is not inputted directly by the expert, but rather the system will learn the knowledge from what the expert did to the previous cases.This research takes image classification as the problem to be solved.As the knowledge development technique, we build decision tree by using C4.5 algorithm.Variables used for building the decision tree are the image visual features.…”
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Classification of strategies for solving programming problems using Aol sequence analysis
Published 2019“…This eye tracking study examines participants’ visual attention when solving algorithmic problems in the form of programming problems. …”
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Hybrid conjugate gradient using exact line search in photovoltaic system / Muhammad Ariiq Iqbaal Azizul Firdaus
Published 2025“…There are four hybrid CG coefficients used in this study, which are PRPLAMR, PRPRMIL, PRPLS and PRPHS. …”
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Chemometrics analysis for the detection of dental caries via ultraviolet absorption spectroscopy / Katrul Nadia Basri
Published 2023“…The best performance obtained using Savitzky-Golay smoothing and LDA algorithms after the wavelength selection with the accuracy reported of 0.90. …”
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Human body electromagnetic radiation: the physiological characteristic for post stroke patients / Ros Shilawani S. Abdul Kadir
Published 2018“…Next, the classification algorithm of k-nearest neighbor (KNN) and artificial neural network (ANN) are applied to discriminate between the samples and between their body segments. …”
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14
Study of hand gesture recognition using impulse radio ultra wideband (IRUWB) radar sensor
Published 2023“…These include exploring recognition of gestures performed by two hands simultaneously, scalability to different environments, optimal sensor placement, and addressing user variability. Seven classification algorithms (K-Nearest Neighbour, Logistic Regression, Naive Bayes, Gradient Boosting, AdaBoost, Bagging, and Linear Discriminant Analysis) were meticulously explored for hand gesture recognition. …”
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15
Application of Hybrid Evolutionary Algorithm and thematic map for rule set generation and visualization of chlorophyta abundance at Putrajaya lake / Lau Chia Fong
Published 2013“…This study describes application of a hybrid combination of hybrid evolutionary algorithm (HEA) and thematic map visualization technique in modeling, predicting and visualization of selected algae division growth, Chlorophyta for tropical Putrajaya Lakes and Wetlands (Malaysia). …”
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Bayesian network of influence of sociodemographic variables on dengue related knowledge, attitude, and practices in selected areas in Selangor, Malaysia
Published 2019“…The data collected was used to learn the structure of BN via some known algorithms using R programming language. …”
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ENGINEERING DESIGN WITH PSO ALGORITHM
Published 2019“…It assists design engineers as it gives a clearer visualization to predict which value of the variables gives a best produced result. …”
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Final Year Project -
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The urban growth images obtained are analysed to improve existing classification algorithms. The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The comparison showed that, the accuracy of the unsupervised classification map with value of 88.4% that was generated by using the cluster labelling algorithm was slightly more than the maximum-likelihood supervised classification map with value of 87.5%. …”
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