Search Results - (( data application testing algorithm ) OR ( parameters detection method algorithm ))
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Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff
Published 2014“…The new algorithm is tested on simulated and real data where the results show it is capable of detecting fraud activities. …”
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Failure detection analysis of grid-connected photovoltaic systems in tropical climate region / Nurmalessa Muhammad @ Atan
Published 2020“…Filtration and identification processes were performed to ensure the selection of reliable data. The FD algorithm has employed mathematical and statistical approaches to establish the relationship between the parameters. …”
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Evaluation of the Transfer Learning Models in Wafer Defects Classification
Published 2022“…Transfer Learning is one of the common methods. Various algorithms under Transfer Learning had been developed for different applications. …”
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Conference or Workshop Item -
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Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network
Published 2009“…On the other hand, when we use computers to reduce uncertainty, the computer itself can become an expert in a specific field through a variety of methods. One such method is machine learning, which involves computer algorithm to capture hidden knowledge from data. …”
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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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HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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Final Year Project -
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Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data
Published 2014“…In order to make all this in a ubiquitous form factor, the algorithm for classification and detection of the pre-seizure conditions should be tremendously simple for processing the signal in a low cost ubiquitous microcontroller. …”
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Edge detection of MRI images using artificial neural network
Published 2017“…Discussion The proposed ANN based edge detection produce better image segmentation for MRI images compared to other traditional edge detection algorithms. …”
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The largest studentized residual test for bad data identification in state estimation of a power system
Published 2015“…A six-bus power system data is used for the application of LSR test for detecting and identifying the gross errors in the processed measurements. …”
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Embedded Fuzzy Classifier for Detection and Classification of Preseizure State Using Real EEG Data
Published 2013“…In order to make all this in a ubiquitous form factor, the algorithm for classification and detection of the pre-seizure conditions should be tremendously simple for processing the signal in a low cost ubiquitous microcontroller. …”
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Book Section -
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Image Splicing Detection With Constrained Convolutional Neural Network
Published 2019“…It is shown that CNN with constrained convolution algorithm can be used as a general image splicing detection task.…”
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Nonlinear vibration based modeling for damage detection of reinforced concrete beams / Muhammad Usman Hanif
Published 2018“…The nonlinear behavior, in the form of nonlinear vibration characteristics, was used in proposing a damage detection algorithm which doesn’t rely on the baseline data of the structure. …”
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Thesis -
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Vision-Based Autonomous Vehicle Driving Control System
Published 2005“…In this study, all the methods have been tested on video data and the experimental results have demonstrated a fast and robust system.…”
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Vision-based autonomous vehicle driving control system
Published 2005“…In this study, all the methods have been tested on video data and the experimental results have demonstrated a fast and robust system.…”
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Robust Estimation Methods And Outlier Detection In Mediation Models
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Translating conventional wisdom on chicken comb color into automated monitoring of disease-infected chicken using chromaticity-based machine learning models
Published 2024“…These works have shown that, despite using only the optical chromaticity of the chicken comb as the input data, the developed models (95% accuracy) have performed exceptionally well, compared to other reported results (99.469% accuracy) which utilize more sophisticated input data such as morphological and mobility features. …”
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Portable Stress Detection System for Autistic Children Using Fuzzy Logic
Published 2024journal::journal article
