Search Results - (( program segmentation learning algorithm ) OR ( parallel optimisation system algorithm ))
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Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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ROA-CONS: raccoon optimization job scheduling
Published 2021“…It describes a new scheduling approach, which is a combination of an updated conservative backfilling approach further optimised by the raccoon optimisation algorithm. This algorithm also proposes a technique of selection that combines job waiting and response time optimisation with user fairness. …”
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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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STATISTICAL FEATURE LEARNING THROUGH ENHANCED DELAUNAY CLUSTERING AND ENSEMBLE CLASSIFIERS FOR SKIN LESION SEGMENTATION AND CLASSIFICATION
Published 2021“…A profound algorithm comprising of preprocessing in CIELAB color space and Delaunay triangulation based clustering along with Particle Swarm Optimization (PSO) is proposed for the segmentation. …”
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Fruit-Fly Based Searching Algorithm For Cooperative Swarming Robotic System
Published 2013“…A number of benchmark function processes were conducted to assess the performance of proposed FOA (Fly Optimisation Algorithm).…”
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Fostering motivation in TVET students: the role of learner-paced segments and computational thinking in digital video learning
Published 2024“…This study aims to address this gap by examining how learner-paced predefined segments and CT algorithmic thinking can impact TVET students' perceived motivation. …”
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Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu
Published 2005“…There are three main programs work together. The programs are back-propagation neural network program, training and performance program and recognition program. …”
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A review on sentiment analysis model Chinese Weibo text
Published 2020“…For traditional machine learning, there are 2 mainly aspects of innovation: Simultaneous classifier (Adoboost+SVM) and Improvement of classical classification algorithm. …”
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Proceedings -
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Hyper-heuristic approaches for data stream-based iIntrusion detection in the Internet of Things
Published 2022“…Therefore, the core classifier in the hyper-heuristic approach of Intrusion Detection System (IDS) is developed to the parallel structure NN. …”
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Five-level single source voltage converter controlled using selective harmonic elimination
Published 2018“…The generated non-linear transcendental equations are solved using an optimised Genetic algorithms to find the switching angles. …”
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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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Ump Intelligent Chatbot Using Dialogflow
Published 2022“…To create such a chatbot, a machine learning algorithm is used to learn the human language that is mainly used during such conversations. …”
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Undergraduates Project Papers -
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Validation of deep convolutional neural network for age estimation in children using mandibular premolars on digital panoramic dental imaging / Norhasmira Mohammad
Published 2022“…The semi-automated dental staging system developed in this study is based on the Malay children’s population and uses a brain-inspired learning algorithm termed "deep learning". The methodology is comprised of four major steps: image preprocessing, which adheres to the inclusion criteria for panoramic dental radiographs, segmentation, and classification of mandibular premolars according to Demirjian's staging system using the Dynamic Programming-Active Contour (DP-AC) method and Deep Convolutional Neural Network (DCNN), respectively, and statistical analysis. …”
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Efficient reconfigurable architectures for 3-D medical image compression
Published 2010“…Using DPR, several large systems are mapped to small hardware resources, and the area, power consumption as well as maximum frequency are optimised and improved. …”
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