Search Results - (( parameter evaluation method algorithm ) OR ( code classification issues algorithm ))
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Crow Search Freeman Chain Code (CS-FCC) feature extraction algorithm for handwritten character recognition
Published 2023“…With so many algorithms developed to improve classification accuracy, interest in feature extraction in Handwritten Character Recognition (HCR) has increased. …”
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Conference or Workshop Item -
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Automatic multilevel medical image annotation and retrieval
Published 2008“…To address third issue, automatic multilevel code generation is proposed for image classification and multilevel image annotation. …”
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Genetic algorithm fuzzy logic for medical knowledge-based pattern classification
Published 2023Article -
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Coastal Priority Ranking in Oil Spill Response Decision Support Mechanism
Published 2008“…Results were verified to present the inclusiveness, accuracy, and system algorithm. The verification activity involved exploring the knowledge base, coding of reasoning processes / inference engine, technical performance, ability for development, and interface. …”
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Thesis -
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Phishing image spam classification research trends: Survey and open issues
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023Conference Paper -
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Taguchi-Grey Relational Analysis Method for Parameter Tuning of Multi-objective Pareto Ant Colony System Algorithm
Published 2023“…The gray relational grade (GRG) performance metric and the Friedman test were used to evaluate the algorithm’s performance. The Taguchi-GRA method that produced the new values for the algorithm’s parameters was shown to be able to provide a better multi-objective generator maintenance scheduling (GMS) solution. …”
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Evaluation of lightning current parameters using measured lightning induced voltage on distribution power lines
Published 2019“…In this paper, an algorithm had been proposed to evaluate the lightning current parameters using measured voltage from overhead distribution lines based on lightning location obtained from lightning location system. …”
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Conference or Workshop Item -
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A multilayered convolutional sparse coding framework for modeling of pooling operation of convolution neural networks
Published 2019“…The multilayered version of CSC(ML-CSC) is shown to be connected to forward pass of CNNs and dictionary learning and sparse coding algorithms of this model are analyzed for solving classification and inverse problems in image processing. …”
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Proceeding Paper -
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…This comparative study aims to investigate and compare the effectiveness of the inversed control parameter in the proposed methods against the original algorithms in terms of the number of selected features and the classification accuracy. …”
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Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…This comparative study aims to investigate and compare the effectiveness of the inversed control parameter in the proposed methods against the original algorithms in terms of the number of selected features and the classification accuracy. …”
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Improving hand written digit recognition using hybrid feature selection algorithm
Published 2022“…While mRMR was capable of identifying a subset of features that were highly relevant to the targeted classification variable, it still carry the weakness of capturing redundant features along with the algorithm. …”
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Final Year Project / Dissertation / Thesis -
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Evaluation of Lightning Current Using Inverse Procedure Algorithm.
Published 2013“…The proposed method considers on all electromagnetic fields components and can evaluate full shape of current, velocity and constant parameters of current models in contrast with previous studies. …”
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Deep learning based emotion recognition for image and video signals: matlab implementation
Published 2021“…This book is carried out to develop an image and video-based emotion recognition model using CNN for automatic feature extraction and classification with Matlab sample codes. Five emotions are considered for recognition: angry, happy, neutral, sad, and surprise, compared to previous algorithms. …”
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