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1
Gas Identi cation by Using a Cluster-k-Nearest-Neighbor
Published 2009“…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
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2
Image clustering comparison of two color segmentation techniques
Published 2010“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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Thesis -
3
Improving the tool for analyzing Malaysia’s demographic change: data standardization analysis to form geo-demographics classification profiles using k-means algorithms
Published 2016“…Clustering is one of the important methods in data exploratory in this era because it is widely applied in data mining.Clustering of data is necessary to produce geo-demographic classification where k-means algorithm is used as cluster algorithm. …”
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4
Automatic Number Plate Recognition on android platform: With some Java code excerpts
Published 2016“…On the other hand, the traditional algorithm using template matching only obtained 83.65% recognition rate with 0.97 second processing time. …”
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Book -
5
Development of a syncope classification algorithm from physiological signals acquired in tilt-table test
Published 2023“…Features that selected for the classification is mean of systolic and diastolic blood pressure, standard deviation of real variability of diastolic blood pressure, and the mean of systolic blood pressure in low and high frequency ratio. …”
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6
Machine learning classifications of multiple organ failures in a malaysian intensive care unit
Published 2024“…This study aims to perform the classification of multiple organ failures using machine learning algorithms based on SOFA score. …”
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7
Machine Learning Classifications of Multiple Organ Failures in a Malaysian Intensive Care Unit
Published 2025“…This study aims to perform the classification of multiple organ failures using machine learning algorithms based on SOFA score. …”
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8
Development of seven segment display recognition using TensorFlow on Raspberry Pi
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Proceeding Paper -
9
A machine learning approach of predicting high potential archers by means of physical fitness indicators
Published 2019“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. However, the application of k-NN for prediction and classification in specific sport is still in its infancy. …”
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10
A machine learning approach of predicting high potential archers by means of physical fitness indicators
Published 2019“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. However, the application of k-NN for prediction and classification in specific sport is still in its infancy. …”
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11
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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12
HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…The algorithm gives a mean accuracy of 84% out of 125 test images.…”
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Final Year Project -
13
Lightning fault classification for transmission line using support vector machine
Published 2023“…Overall, SVM algorithm performed better than k-NN in terms of classification accuracy, achieving a value of 97.10% compared to k-NN’s 70.60%. …”
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14
Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification
Published 2020“…The last phase involves developing a new fusion algorithm using SVM and Fuzzy K-Means Clustering (FKM) algorithms for Sentinel 2 data to enhance LCM accuracy. …”
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Thesis -
15
The Identification of High Potential Archers Based on Fitness and Motor Ability Variables: A Support Vector Machine Approach
Published 2018“…Support Vector Machine (SVM) has been shown to be an effective learning algorithm for classification and prediction. However, the application of SVM for prediction and classification in specific sport has rarely been used to quantify/discriminate low and high-performance athletes. …”
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16
Classification and quantification of palm oil adulteration via portable NIR spectroscopy
Published 2017“…In order to remove the uninformative variables, variable selection using cumulative adaptive reweighted sampling (CARS) has been performed. …”
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17
HEp-2 cell images classification based on statistical texture analysis and fuzzy logic
Published 2014“…The extracted features are then used as an input parameter to classify five staining patterns by using fuzzy logic. A working classification algorithm is developed and gives a mean accuracy of 84 out of 125 test images. …”
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Conference or Workshop Item -
18
Lightning Fault Classification for Transmission Line Using Support Vector Machine
Published 2024“…Overall, SVM algorithm performed better than k-NN in terms of classification accuracy, achieving a value of 97.10% compared to k-NN's 70.60%. …”
Conference Paper -
19
Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data
Published 2022“…The classical correlation estimators that employ the sample mean of the dependent and independent variables are known to be affected by outliers. …”
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20
Classification and quantification of palm oil adulteration via portable NIR spectroscopy
Published 2024“…In order to remove the uninformative variables, variable selection using cumulative adaptive reweighted sampling (CARS) has been performed. …”
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