Search Results - (( parameter defect classification algorithm ) OR ( java application optimisation algorithm ))
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1
Software defect prediction framework based on hybrid metaheuristic optimization methods
Published 2015“…The classification algorithm is a popular machine learning approach for software defect prediction. …”
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2
Using the bees algorithm to optimise a support vector machine for wood defect classification
Published 2007“…The objective of the work was to find the best combination of SVM parameters and data features to maximize defect classification accuracy. …”
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3
Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…In this paper, an evaluation for these transfer learning to be applied in wafer defect detection. The objective is to establish the best transfer learning algorithms with a known baseline parameter for Wafer Defect Detection. …”
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4
The formulation of a transfer learning pipeline for the classification of the wafer defects
Published 2023“…Automated processes have been used commonly in recent years, with the judgement done by using conventional image processing algorithm. However, limitations such as robustness and difficulty in setting up the parameters required for image processing algorithm encourages the investigation in using Deep learning classification in detecting the wafer defects. …”
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5
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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6
Photogrammetric low-cost unmanned aerial vehicle for pothole detection mapping / Shahrul Nizan Abd Mukti
Published 2022“…The lowest error of pothole polygon classification is 0.016m² from classification of Mahalanobis distance algorithm with NIR + red edge + red or Green + red edge + red combination. …”
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7
Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin
Published 2011“…The Resilient Backpropagation (RPROP) algorithm is used to train the network. The optimized learning parameter used is 0.07 and the network has best performance when hidden neurons equal to 220. …”
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8
Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…In this research work, the motivation is to develop an autonomous learning model based on the hybridization of an adaptive ANN and a metaheuristic algorithm for optimizing ANN parameters so that the network could perform learning and adaptation in a more flexible way and handle condition classification tasks more accurately in industries, such as in power systems. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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11
Training feedforward neural networks for fault diagnosis of ball bearing
Published 2018“…The results show that the proposed approach produces comparable classification accuracy as parameters of the FNNs were optimized systematically using CFS algorithm.…”
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12
Computer aided diagnoses for detecting the severity of Keratoconus
Published 2024“…Problem: Corneal topography instruments have limited parameter constraints for calculating precise defect ratios on the basis of the cone base area of the anterior axial curvature map for patients with Keratoconus (KC). …”
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13
Real-time oil palm fruit bunch ripeness grading system using image processing techniques
Published 2013“…External features and properties such as colour,texture, shape, and size are good indicators for parameters like ripeness and defects. Grading varies among graders and is often inconsistent. …”
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