Search Results - (( developing implementation learning algorithm ) OR ( based application customization algorithm ))
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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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Predicting pneumonia and region detection from X-Ray images using deep neural network
Published 2021“…Along the way, many machine learning algorithms have been proposed to predict and identify various kinds of diseases. …”
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3
Fraud detection in shipping industry based on location using machine learning comparison techniques
Published 2023“…A number of popular existing algorithms were used to execute the model developed in Rapid tool such as Naïve Bayes , Neural Net , Deep Learning, Decision Tree, Logistic Regression, SVM and k-NN. …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural networkbwith open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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Quality prediction and classifcation of resistance spot weld using artifcial neural network with open‑sourced, self‑executable andGUI‑based application tool Q‑Check
Published 2023“…In this study, application tool using open-sourced and customized algorithm based on artifcial neural networks (ANN) was developed to enable better, fast, cheap and practical predictions of major parameters such as welding time, current and electrode force on tensile shear load bearing capacity (TSLBC) and weld quality classifcations (WQC). …”
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Automate customer support handling E-Commerce enquiry using ChatGPT
Published 2024“…The methodology involves the design of a distributed system architecture for scalability and efficient task distribution. Machine Learning-based Named Entity Recognition (NER) is employed to identify and extract specific entities, while contextual analysis algorithms determine message relevance for summarization. …”
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The Role of Machine Learning and Deep Learning Approaches for the Detection of Skin Cancer
Published 2023“…Machine learning (ML) can enhance a dermatologist’s work, from diagnosis to customized care. …”
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CNN integrated mobile application: food image recognition for recipe generation
Published 2025“…The application provides users with a wide range of meal alternatives that are customized to their available ingredients by retrieving relevant recipes from external databases such as the Spoonacular API based on the recognized ingredients. …”
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Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…In the algorithm development a step-by-step example of the algorithm implementation is presented and then successfully implemented in Lego Mindstorm obstacle avoiding mobile robot as a proof of concept implementation of the hybrid AI algorithm. …”
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17
Incremental learning for large-scale stream data and its application to cybersecurity
Published 2015“…In Chapter 2, we propose a new algorithm based on incremental Radial Basis Function Network (RBFN) to accelerate the learning in stream data. …”
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Digital assistant for workspace apps
Published 2022“…The proposed system will be achieved by applying machine learning to train the digital assistant model for it can study and execute every Teams’ function or the function combinations and allow user customization on its steps to complete certain task. …”
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Final Year Project / Dissertation / Thesis -
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Development of image recognition system for steel defects detection
Published 2022“…For the rusting detection algorithm, a deep learning model, Single Shot Detector (SSD), was trained to detect and crop the hot rolled steel from the input image for colour detection. …”
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Final Year Project / Dissertation / Thesis
