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Modern fuzzy min max neural networks for pattern classification
Published 2019“…Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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Thesis -
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Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks
Published 2014“…EFMM and EFMM2, are proposed to address a number of limitations in the original FMM learning algorithm. In EFMM, three heuristic rules are introduced to improve the hyperbox expansion, overlap test, and contraction processes. …”
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Kernel and multi-class classifiers for multi-floor wlan localisation
Published 2016“…Unlike the classical kNN algorithm which is a regression type algorithm, the proposed localisation algorithms utilise machine learning classification for both linear and kernel types. …”
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Statistical data preprocessing methods in distance functions to enhance k-means clustering algorithm
Published 2018“…The suggested approaches are called new approach to min-max (NAMM) and decimal scaling (NADS). The Hybrid mean algorithms which are based on spherical clusters is also proposed to remedy the most significant limitation of the K-Means and K-Midranges algorithms. …”
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ANALYSIS OF BIOSENSOR PHYSIOLOGICAL SIGNALS FOR ASSESSMENT OF NEUROLOGICAL STATUS
Published 2018“…All the data signals of the 20 subjects will then be processed with features extraction method using mean, maximum (Max), minimum (Min), mean absolute deviation (MAD), Standard deviation (STD), interquartile range (IQR) and summation (Sum). …”
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Final Year Project -
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Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using k-Nearest Neighbour (k-NN)
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Dense-cluster based voting approach for license plate identification
Published 2018“…Furthermore, the recognition results from classification show that recognition rate improves significantly compared to prior classification.…”
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Automated plaque classification using computed tomography angiography and Gabor transformations
Published 2019“…The features were then ordered based on the F-value and input to numerous classification methods to achieve the best classification accuracy with the least number of features. …”
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Article -
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Predicting STEM academic performance in secondary schools: data mining approach
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Conference or Workshop Item -
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Classification of compressive strength grades for lightweight aggregate concrete with palm oil fuel ash (POFA) using kNearest Neighbour (k-NN)
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Malaysian license plate recognition system using Convolutional Neural Network (CNN) on web application / Nur Farahana Mahmud
Published 2022“…The obtained sample image will first undergo pre-processing and character extraction. 3 layers of a Convolutional Neural Network (CNN) model that contain convolutional, max pooling, flatten and dense were created and further trained. …”
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Student Project -
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Assessment of forest aboveground biomass estimation from superview-1 satellite image using machine learning approaches / Azinuddin Mohd Asri
Published 2022“…The Random Forest algorithm was the best algorithm compared to the artificial neural network, which produced the highest R2 (0.998) and lowered RSME (55.067). …”
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15
MiMaLo: advanced normalization method for mobile malware detection
Published 2022“…An application used to be mounted on mobile gadget to gather facts and processed them to get dataset. This research used data mining classification approach method and validates it using ten fold cross validation. …”
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A multilayered convolutional sparse coding framework for modeling of pooling operation of convolution neural networks
Published 2019“…The multilayered version of CSC(ML-CSC) is shown to be connected to forward pass of CNNs and dictionary learning and sparse coding algorithms of this model are analyzed for solving classification and inverse problems in image processing. …”
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Proceeding Paper -
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Iot health monitoring system for self quarantined covid-19 patients
Published 2022“…Then to get the temperature reading we use some algorithm to calculate the temperature reading from sensor. …”
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Undergraduates Project Papers -
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease
Published 2021“…The machine learning algorithm consistently performs well when presented with a well-balanced dataset. …”
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Automated diagnosis of diabetes using entropies and diabetic index
Published 2016“…These redundant features are eliminated by using six feature selection algorithms: Student's t-test, Receiver Operating Characteristic Curve (ROC), Wilcoxon signed-rank test, Bhattacharyya distance, Information entropy and Fuzzy Max-Relevance and Min-Redundancy (MRMR). …”
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