Search Results - (( program segmentation models algorithm ) OR ( java application clustering 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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A Toolkit for Simulation of Desktop Grid Environment
Published 2014“…The prototypes will be developed using JAVA language united with a MySQL database. Core functionality of the simulator are job generation, volunteer generation, simulating algorithms, generating graphical charts and generating reports. …”
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Final Year Project -
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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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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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A review on sentiment analysis model Chinese Weibo text
Published 2020“…In feature extraction, the Lexicon-based Model, Machine learning Model and deep learning Model usually was used. …”
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Proceedings -
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Leaf condition analysis using convolutional neural network and vision transformer
Published 2024“…Through the use of a hybrid deep learning model that combines vision transformer and convolutional neural networks for classification, the algorithm can be optimized. …”
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Nearfield Electromagnetic Imaging Technique For Brain Tumour Detection
Published 2019“…Two type of results exhibits in this thesis; FTBS technique and FBTS technique with image segmentation. The results obtained without image segmentations able to detect a smaller tumour. …”
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Implementation of RBG-HS-CbCr skin colour model using mobile python PyS60
Published 2009“…These algorithms are often tested and applied on PC. …”
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Final Year Project Report / IMRAD -
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Road lane detection using h-maxima and improved hough transform
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Conference or Workshop Item -
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Modeling Of Electrical Distribution Networks With Particle Swarm Optimization Technique For The Improvement Of Voltage Profile And Loss Reduction
Published 2016“…The data of series impedance is also used to investigate power flow in all segments in the distribution system. Therefore, modified Carson's equations have been utilized in this study to calculate series impedance of both overhead lines and underground cables using MATLAB program for getting more accurate results. …”
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A headway and order scheme based mixed integer goal programming model for railway rescheduling / Zuraida Alwadood
Published 2017“…A novel heuristic algorithm named as Headway and Order Scheme (HOS) is introduced to solve the rescheduling model. …”
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Vision-Based Autonomous Vehicle Driving Control System
Published 2005“…The important contribution of this study is the development of vehicle lane detection and tracking algorithm based on colour cue segmentation, Canny edge detection and Hough transform. …”
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Vision-based autonomous vehicle driving control system
Published 2005“…The important contribution of this study is the development of vehicle lane detection and tracking algorithm based on colour cue segmentation, Canny edge detection and Hough transform. …”
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An integrated model of automated elementary programming feedback using assisted and recommendation approach
Published 2017“…Meanwhile, similar difficulty groups of the computer programs were generated using a K-Means clustering algorithm that was enhanced with ranking consideration. …”
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