Search Results - (( intelligence based safety algorithm ) OR ( intelligence based learning algorithm ))
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Artificial Intelligence (AI) in the art and design industry / Fahmi Samsudin
Published 2023“…It encompasses different types, such as rule-based AI using if-then statements for decision-making, machine learning which employs algorithms to analyze and learn from data, and deep learning utilizing artificial neural networks to learn from extensive datasets. …”
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A review of object detection in traffic scenes based on deep learning
Published 2024“…This survey is based on the theory of deep learning. It systematically summarizes the Development and current research status of object detection algorithms, and compare the characteristics, advantages and disadvantages of the two types of algorithms. …”
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Development of fault detection and diagnosis for reactor cooling system by using artificial intelligent techniques
Published 2023“…In realizing this, a model-based FDD system, a system modelling and fault diagnosis algorithm need to be studied. …”
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Ethical concerns about the applications of artificial intelligence in healthcare practices: an explanatory review
Published 2021“…Artificial intelligence technologies that benefited healthcare include machine learning, natural language processing, rule-based expert system, physical robots, and robotics process automation. …”
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines
Published 2020“…The BayesNet provides the best integrated MLADR fault classifier model better at a 5 % significance level than other deployed algorithms in the intelligent supervised learning model realization. …”
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Thesis -
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Deep-learning-based detection of missing road lane markings using YOLOv5 algorithm
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Proceeding Paper -
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Artificial Intelligence Forecasting for Transmission Line Ampacity
Published 2023“…Dynamic line ratings can be modelled physically, statistically, and using machine learning and artificial intelligence. This chapter aims to address the implementation of machine learning and artificial intelligence algorithms in predicting the DLR of transmission systems. …”
Book Chapter -
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Intelligent traffic lights using Q-learning
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Proceeding Paper -
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Computer vision that can ‘see’ in the dark
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Artificial intelligence revolutionising the automotive sector: A comprehensive review of current insights, challenges, and future scope
Published 2025“…The review highlights that AI has significantly expedited the development of autonomous vehicles regarding navigation, decision-making, and safety features through the use of advanced algorithms and deep learning structures. …”
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Deep learning-based vehicular engine health monitoring system utilising a hybrid convolutional neural network/bidirectional gated recurrent unit
Published 2024“…This paper introduces a hybrid deep learning-based vehicular engine health monitoring system (VEHMS) decision model using Deep CNN (convolutional neural network)-BiGRU (bi-directional gated recurrent unit). …”
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Apply and optimize machine learning algorithms for estimating battery health
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Final Year Project / Dissertation / Thesis -
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Deep learning based human presence detection
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Artificial intelligence-driven vehicle fault diagnosis to revolutionize automotive maintenance: A review
Published 2024“…We focus on reviewing relevant literature in the field of machine learning as well as deep learning algorithms for fault diagnosis in engines, lifting systems (suspensions and tires), gearboxes, and brakes, among other vehicular subsystems. …”
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Spear- phishing attack detection using artificial intelligence
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Final Year Project / Dissertation / Thesis -
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A comparative study of supervised machine learning approaches for slope failure production
Published 2023“…The prediction result from testing data was validated based on statistical analysis. The result shows that SVM model has outperformed DT model by giving the prediction accuracy of 97%. ith the advent of technology and the introduction of computational intelligent methods, the prediction of slope failure using the machine learning (ML) approach is rapidly growing for the past few decades. …”
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