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Enhancing benthic habitat mapping: A review of integrating satellite and side scan sonar data for improved classification accuracy
Published 2024“…It is also expected that the review will provide valuable insights into data and classification decisions regarding the use of satellite imagery and acoustic data in future coral reef community mapping.…”
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Classification Algorithms and Feature Selection Techniques for a Hybrid Diabetes Detection System
Published 2021“…The proposed method has three steps: preprocessing, feature selection and classification. Several combinations of Harmony search algorithm, genetic algorithm, and particle swarm optimization algorithm are examined with K-means for feature selection. …”
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Classification models for higher learning scholarship award decisions
Published 2018“…Five algorithms were employed to develop a classification model in determining the award of the scholarship, namely J48, SVM, NB, ANN and RT algorithms. …”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han
Published 2018“…Hitherto, the majority of computer vision approaches have been focused on designing sophisticated algorithms to achieve a robust feature representation for plant data. …”
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Financial time series predicting using machine learning algorithms
Published 2013“…In the second proposed framework, Linear Regression Line (LRL) is utilised to identify the trend patterns from historical financial time series, which is supported by ANN and SVM for classification process separately. Subsequently, Dynamic Time Warping (DTW) algorithm is utilised through brute force to predict the trend movement. …”
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Digital economy tax compliance model in Malaysia using machine learning approach
Published 2021“…Based on the validation of training data with the presence of seven single classifier algorithms, three performance improvements have been established through ensemble classification, namely wrapper, boosting, and voting methods, and two techniques involving grid search and evolution parameters. …”
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Automated classification radiograph of Periodontal bone loss using deep learning
Published 2025“…The training process was conducted using MATLAB on a Dell computer equipped with a GeForce RTX 4060 GPU. Image data augmentation was applied to increase dataset diversity. …”
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Handgrip strength evaluation using neuro fuzzy approach
Published 2010“…The fuzzy model based on the membership function, fed in by the neural network will intelligently classify the data. The results indicate that the classification accuracy of normal and pathological patients are 90 and 75 respectively. …”
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Robust and reliable dual the classification system with error compensation module
Published 2014“…Test using simulated data shows that the algorithm can maintain 100% accuracy when two errors are present. …”
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Developing framework for natphoric computer-aided web-based kansei engineering / Mohammad Bakri Che Haron
Published 2013“…The Natphoric algorithm learns the process done by training with sets of training data from previous KE research works. …”
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Exploring the impact of social media on political discourse: a case study of the Makassar mayoral election
Published 2024“…To increase the accuracy and efficiency of text mining operations, especially in result validation, text clustering, and classification, the k-means algorithm and support vector machines (SVM) were used. …”
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Intelligent motion planning of a mobile robot by using convolutional neural network / Siti Asmah Abdullah
Published 2019“…By the path reference created by A* algorithm the robot is capable in optimizing its path to reach the designated destination. …”
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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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