Search Results - (( java interaction effects algorithm ) OR ( program segmentation learning algorithm ))
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A random search based effective algorithm for pairwise test data generation
Published 2011“…Java program has been used to test the performance of the algorithm. …”
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Conference or Workshop Item -
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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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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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EasyA: Easy and effective way to generate pairwise test data
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Conference or Workshop Item -
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Teaching and learning via chatbots with immersive and machine learning capabilities
Published 2019“…In order to address these shortcomings, seven text-based conversational chatbots for the students to learn Java in an interactive and engaging manners had been built. …”
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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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Input-output based relation combinatorial testing using whale optimization algorithm for generating near optimum number of test suite
Published 2025“…Experimental results indicate that WOA outperforms or matches the effectiveness of these strategies in generating smaller test suites, particularly for higher interaction strengths. …”
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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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Comparative Analysis of Cervical Cell Classification Using Machine Learning Algorithms
Published 2026journal::journal article -
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Web-based RIG performance reporting system using interactive visualization techniques / Amir Hambaly Nasaruddin
Published 2019“…The result of this project is all algorithm for visualizing data is functioning and the output produced from the system is correct and effective. …”
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Thesis -
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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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Dynamic force-directed graph with weighted nodes for scholar network visualization
Published 2022“…The approach is realized by creating a web-based interface using D3 JavaScript algorithm that allows the visualization to focus on how data are connected to each other more accurately than the conventional lines of data seen in traditional data representation. …”
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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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