Search Results - (( solution detection method algorithm ) OR ( parameter evaluation method algorithm ))
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1
Single Fitness Function to Optimize Energy using Genetic Algorithms for Wireless Sensor Network
Published 2024journal::journal article -
2
Optimize and deploy machine learning algorithms on embedded devices for manufacturing applications
Published 2025“…Not to say the difficulty in deploying either artificial intelligence or deep learning in embedded environments due to significant parameters size and computational complexity. In recent studies, we seen developers and researchers proposing solutions on deep learning algorithms like YOLO, EfficientNet, CNN, MobileNet etc. …”
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Final Year Project / Dissertation / Thesis -
3
Forward-Backward Time Stepping with Automated Edge-preserving Regularization Technique for Wood Defects Detection
Published 2019“…Therefore, the microwave imaging technique is proposed to detect the wood defects. In this thesis, Forward-Backward Time-Stepping (FBTS) method is applied to microwave imaging wood defect detection application. …”
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4
Power System State Estimation In Large-Scale Networks
Published 2010“…Also the WLS algorithm is modified to include Unified Power Flow Controller (UPFC) parameters. …”
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5
Customer analysis with machine vision
Published 2023“…To evaluate the performance of existing detection models, metrics such as accuracy, precision, recall, F1 score, false detection rate, model size, and parameters are used. …”
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Final Year Project / Dissertation / Thesis -
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Defect detection of GFRP composites through long pulse thermography using an uncooled microbolometer infrared camera
Published 2024“…The TC success rate reached 0.91 for detecting FBH depth defects in raw images, which improved significantly after post-processing using Canny edge detection and Hough circle detection algorithms. …”
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Reliability study of L1-Norm Adjustment in examining the inconsistencies of cadastral record / Nur Alya Nasuha Azizan
Published 2023“…The dependence on mean value in deriving adjusted parameters has constrained the LSE solutions, making the algorithm prone to blunders. …”
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Student Project -
8
New global maximum power point tracking and modular voltage equalizer topology for partially shaded photovoltaic system / Immad Shams
Published 2022“…Only one dynamic variable is used as a tuning parameter reducing the complexity of the algorithm. …”
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Thesis -
9
A New Approach of Optimal Search Solution in Particle Swarm Optimization (PSO) Algorithm for Object Detection Method
Published 2018“…Therefore, to overcome the several problems associated with the object detection method, a new approach in Particle Swarm Optimization (PSO) algorithm for optimal search solution as an alternative method to detect of object tracking quickly, precisely and accurately. …”
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Methods of intrusion detection in information security incident detection: a comparative study
Published 2018“…These algorithms and methods provide fast and high rate of detection. …”
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Conference or Workshop Item -
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Vehicle detection for vision-based intelligent transportation systems using convolutional neural network algorithm
Published 2022“…Software based solutions using traditional algorithms such as Histogram of Gradients (HOG) and Gaussian Mixed Model (GMM) are computationally slow and not suitable for real-time traffic detection. )erefore, the paper will review and evaluate different vehicle detection methods. …”
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12
Risk assessment of dengue in Betong Sarawak using simple mathematical model
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13
Power line corridor vegetation encroachment detection from satellite images using retinanet and support vector machine
Published 2023“…Several studies have provided solutions for detecting vegetation encroachment based on satellite images. …”
text::Thesis -
14
Enhanced algorithms for three-dimensional object interpreter
Published 2004“…The linear system is solved using bisection method of total least square approximation. Besides reducing the number of image regularities used and new method to solve the linear system, this study has proposed better solutions in terms of an enhanced thinning algorithm, a modified Freeman chain code algorithm as picture description language, and a new computational comer detection algorithm.…”
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Thesis -
15
Parameter extraction of photovoltaic module using hybrid evolutionary algorithm
Published 2023Conference Paper -
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An efficient anomaly intrusion detection method with feature selection and evolutionary neural network
Published 2020“…Moreover, the value of the solution is evaluated based on the objective function and the Fuzzy C Means (FCM) clustering method used to provide the best results for the overlapping dataset and create the fuzzy membership search domain which includes all possible compromise solutions. …”
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17
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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Enhanced computational methods for detection and interpretation of heart disease based on ensemble learning and autoencoder framework / Abdallah Osama Hamdan Abdellatif
Published 2024“…This thesis presents two innovative methods that holistically address these challenges at algorithmic and data levels to enhance heart disease detection. …”
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19
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 -
20
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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