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DEEP LEARNING ALGORITHM IMPLEMENTATION FOR SHIP DETECTION IN SPOT SATELLITE IMAGES
Published 2019“…The deep-learning algorithm to be deployed is Faster R-CNN and to be implemented using MATLAB. …”
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Final Year Project -
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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Thesis -
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Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection
Published 2024“…The data was gathered using real-time packet capturing tools which were then processed and moved with model development using different deep learning algorithms such as, LSTM, MLP, RNN and Autoencoders. …”
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Analyzing enrolment patterns: modified stacked ensemble statistical learning based approach to educational decision-making
Published 2024“…The study’s primary objectives were to identify the determinants that impacted urban upper-secondary students' enrolment in Additional Mathematics within the Kuantan District, Pahang, Malaysia, and to develop a novel modified stacked ensemble statistical learning-based algorithm based on potential determinants, following the Cross Industry Standard Process for Data Mining (CRISP-DM) data science methodology. …”
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Autonomous path planning robot using geographical information
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Learning Object -
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Mobile app of mood prediction based on menstrual cycle using machine learning algorithm / Nur Hazirah Amir
Published 2019“…It implemented Supervised Learning algorithm with Bayes’ Theorem model for the calculation of mood prediction using Python programming language. …”
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Thesis -
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Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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Thesis -
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Interactive framework for dynamic modelling and active vibration control of flexible structures
Published 2008“…Controller-design strategies, parametric as well as nonparametric, are integrated within this framework. The design and implementation of the interactive learning system incorporating the simulation algorithms, modelling and control strategies, are developed using MATLAB. …”
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Article -
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Analyzing enrolment patterns: Modified stacked ensemble statistical learning-based approach to educational decision-making
Published 2024“…The study’s primary objectives were to identify the determinants that impacted urban upper-secondary students' enrolment in Additional Mathematics within the Kuantan District, Pahang, Malaysia, and to develop a novel modified stacked ensemble statistical learning-based algorithm based on these determinants, following the CRISP-DM data science methodology. …”
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A Divide-and-Distribute Approach to Single-Cycle Learning HGN Network for Pattern Recognition
Published 2010“…Distributed Hierarchical Graph Neuron (DHGN) is a single-cycle learning distributed pattern recognition algorithm, which reduces the computational complexity of existing pattern recognition algorithms by distributing the recognition process into smaller clusters. …”
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Conference or Workshop Item -
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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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Thesis -
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Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots
Published 2006“…Results showed that robot controllers could be successfully developed using the POE-MOEA algorithm. The generated robot controllers allowed the robots to move towards to the light source even the simulation and testing environments are noticeably different.…”
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Research Report -
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Machine learning in predicting anti-money laundering compliance with protection motivation theory among professional accountants
Published 2023“…The research elaborates on the design and implementation of machine learning models based on three algorithms: Decision Tree, Gradient Boosted Tree, and Support Vector Machine. …”
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Innovative smart phone learning system for graphical systems within covid-19 pandemic
Published 2023“…This paper used the Technology Acceptance Model (TAM) as an m-learning model, and Bresenham�s line algorithm is a calculation system implemented by applications. …”
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Preliminary analysis of malware detection in opcode sequences within IoT environment
Published 2020“…Three machine learning algorithms are evaluated and compared for accuracy, precision, recall and F-measure. …”
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A Bayesian parameter learning procedure for nonlinear dynamical systems via the ensemble Kalman filter
Published 2018“…Within the parameter learning steps, the MCMC algorithm requires to perform state estimation for which the target distribution is constructed by using the Ensemble Kalman filter (EnKF). …”
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Design, development and evaluation of a game-based learning application for room housekeeping
Published 2024“…The paper concludes with a discussion on potential enhancements such as incorporating adaptive learning algorithms and multiplayer features to support collaborative learning. …”
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