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1
An improvement of back propagation algorithm using halley third order optimisation method for classification problems
Published 2020“…The efficiency of the proposed methods is compared with the first and second order optimisation method by means of simulation on UCI Machine Learning Repository, Knowledge Extraction Evolutionary Learning and Kaggle dataset. …”
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Thesis -
2
A new hybrid deep neural networks (DNN) algorithm for Lorenz chaotic system parameter estimation in image encryption
Published 2023“…The fitness function used is the correlation function in the SKF algorithm to optimize the cipher image produced using the Lorenz system. …”
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3
The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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4
Odour based human identification and classification using neural networks
Published 2019“…The unsurpassed framework for algorithm learning to be used for human identification can be back propagation learning algorithm named the Levenberg-Marquardt. …”
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5
Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield.
Published 2005“…In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering climate data. …”
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6
Predicting noise-induced hearing loss (NIHL) in TNB workers using GDAM algorithm
Published 2012“…Previously, several modifications were suggested to improve the convergence rate of Gradient Descent Back-propagation algorithm such as careful selection of initial weights and biases, learning rate, momentum, network topology, activation function and ‘gain’ value in the activation function. …”
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7
On some methods of feature engineering useful for craniodental morphometrics of rats, shrews and kangaroos / Aneesha Pillay Balachandran Pillay
Published 2024“…The results showed that the RFE-selected features were able to improve the classification accuracy of the machine learning algorithms. …”
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8
A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. …”
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9
Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine
Published 2023“…In this dissertation, a new vegetation encroachment detection method was proposed by studying the feasibility of using the visible-light band of highresolution satellite images using the RetinaNet deep learning model and Support Vector Machine algorithm (SVM). …”
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10
Development of compound clustering techniques using hybrid soft-computing algorithms
Published 2006“…The hierarchical fuzzy clustering method developed here is far better than a similar implementation of the hard k-means method. …”
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Monograph -
11
A framework for predicting oil-palm yield from climate data
Published 2006“…In this paper we present a robust weighted kernel k-means algorithm incorporating spatial constraints for clustering the data. …”
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Conference or Workshop Item -
12
Artificial neural network implementation on firearm recognition system with respect to ring firing pin impression image
Published 2011“…A two-layer 6-7-5 connections BPNN of sigmoid/sigmoid transfer functions with ‘trainscg’ algorithm was found to yield the best classification result using cross-validation, where 98% of the images were correctly classified according to the pistols used. …”
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Proceeding Paper -
13
Human odour detection approach using machine learning
Published 2019“…The unsurpassed framework for learning algorithm to be used for human identification is Levenberg-Marquardt backpropagation learning algorithm. …”
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14
Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…Hence, this situation is believed in yielding of decreasing the classification accuracy. In this article, we present the exploration on the combination of the clustering based algorithm with an ensemble classification learning. …”
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Article -
15
Firearm recognition based on whole firing pin impression image via backpropagation neural network
Published 2011“…A two-layer 6-7-5 connections BPNN of sigmoid/linear transfer functions with ‘trainlm’ algorithm was found to yield the best classification result using cross-validation, where 96% of the images were correctly classified according to the pistols used. …”
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Book Chapter -
16
Firearm recognition based on whole firing pin impression image via backpropagation neural network
Published 2011“…A two-layer 6-7-5 connections BPNN of sigmoid/linear transfer function with ‘trainlm’ algorithm was found to yield the best classification result using cross-validation, where 96% of the images were correctly classified according to the pistols used. …”
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Proceeding Paper -
17
An Artificial Intelligence-Based Knowledge Management System for Outcome-Based Education Implementing in Higher Education Institutions
Published 2025“…Recommendation system on learning analysis was implemented in a hybrid algorithm combines Rule-based and Content-based filtering algorithms. …”
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18
Pelvic classification based on deep learning algorithm on clinical CT scans in Malaysian population
Published 2023“…This study analysed the Phenice method by utilising 3D CT scans by deep learning algorithm for sex estimation and age estimation. …”
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19
Detection of sweetness level for fruits (watermelon) with machine learning
Published 2020“…The objective of this work is to investigate the sweetness parameter for the fruit’s detection and classification algorithm in machine learnings. This study applies image processing techniques to detect the color and shape of watermelon’s skin for grading based on the sweetness level using K-means clustering method via the Python platform. 13 samples of watermelon images are used to test the functionality of the proposed detection system in this study. …”
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Proceeding Paper -
20
Drone-based surveillance of palm tress ecosystems
Published 2024“…This paper presents a novel surveillance system designed to identify the health status of oil palm trees by leveraging MATLAB object detection and deep learning techniques. The study aims to improve the accuracy and efficiency of palm health detection by integrating MATLAB's initial object recognition with advanced deep learning algorithms. …”
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