Search Results - (( java implementation clustering algorithm ) OR ( program deep learning algorithm ))
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Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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Thesis -
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Image clustering comparison of two color segmentation techniques
Published 2010“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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Novice programmers’ emotion and competency assessments using machine learning on physiological data / Fatima Jannat
Published 2022“…There is also growing interest in modeling machine learning and deep learning algorithms that can learn from user’s data, understand and react to that individual’s affective state. …”
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A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…A simulator for desktop grid environment has been developed using Java as the implementation language due to its wide popularity. …”
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Final Year Project -
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Construction Noise Prediction Using Stochastic Deep Learning
Published 2022“…The programming algorithm of stochastic modelling was executed in MATLAB, whereas the deep learning model was established by using Python 3.6 programming language in Spyder. …”
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Final Year Project / Dissertation / Thesis -
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Deep Reinforcement Learning For Control
Published 2021“…The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. Gathering and evaluating a large amount of data is time and effortintensive. …”
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Detection of in-car-abandoned children via deep learning algorithm / Mohd Farhan Mohd Pauzi
Published 2022“…Therefore, this study aims to detect the existence of "in-car-abandoned children" using deep learning algorithm. A set of children images model captured and then classified into two (2) classes; children and no-children via Convolutional Neural Network (CNN) classifier. …”
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A web-based implementation of k-means algorithms
Published 2022“…Firstly, k-luster could incorporate additional clustering algorithms, or even classification algorithms in the future. …”
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Final Year Project / Dissertation / Thesis -
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Flock optimization algorithm-based deep learning model for diabetic disease detection improvement
Published 2024“…Hence, the research objective is to create an improved diabetic disease detection system using a Flock Optimization Algorithm-Based Deep Learning Model (FOADLM) feature modeling approach that leverages the PIMA Indian dataset to predict and classify diabetic disease cases. …”
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Development of deep learning based user-friendly interface for fruit quality detection
Published 2024“…The implementation of deep learning algorithms has contributed to various applications related to the detection of fruit quality. …”
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Accuracy of advanced deep learning with tensorflow and keras for classifying teeth developmental stages in digital panoramic imaging
Published 2022“…Background: This study aims to propose the combinations of image processing and machine learning model to segment the maturity development of the mandibular premolars using a Keras-based deep learning convolutional neural networks (DCNN) model. …”
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Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
Published 2009“…The development of this architecture is based on several programming language as it involves algorithm implementation on C, parallelization using Parallel Virtual Machine (PVM) and Java for web services development. …”
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Conference or Workshop Item -
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Analysis Of Personal Protective Equipment Classification Method Using Deep Learning
Published 2022“…To avoid a tedious work in manually checking whether workers wear PPE or not, an automatic PPE classifier is constructed by utilizing a deep learning algorithm called Convolutional Neural Network (CNN). …”
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Undergraduates Project Papers -
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An ensemble deep learning classifier stacked with fuzzy ARTMAP for malware detection
Published 2023“…However, legacy anti-malware methods are confronted with millions of potential malicious programs. To combat these threats, intelligent anti-malware systems utilizing machine learning (ML) models are useful. …”
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