Search Results - (( processes detection method algorithm ) OR ( pattern classification methods algorithm ))
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1
Swarm negative selection algorithm for electroencephalogram signals classification
Published 2009“…Therefore, there is a strong need to automate this process. Such automated systems must rely on robust and effective algorithms for detection and prediction. …”
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2
HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…Automated system also saves time and cost as the system is able to process large amount of image data at one time. 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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3
Detecting lung cancer region from CT image using meta-heuristic optimized segmentation approach
Published 2022“…The introduced method detects the overlapping features for optimal edge classification. …”
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4
Performance of Levenberg-Marquardt neural network algorithm in power quality disturbances classification / Adibah I’zzah Mohamad Kasim
Published 2025“…The increasing complexity of modern power systems necessitates advanced methods for detecting and classifying power quality disturbances (PQDs), which impact system reliability and equipment performance. …”
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5
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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6
Intelligent non-destructive classification of josapine pineapple maturity using artificial neural network
Published 2016“…Next, classification index to determine the pineapple maturity level has been applied which are linear classification using thresholding value and artificial neural network adopting pattern recognition method. …”
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7
Hybrid honey badger algorithm with artificial neural network (HBA-ANN) for website phishing detection
Published 2024“…Artificial Neural Network (ANN) is one popular method for website phishing detection. ANN is capable of detecting phishing websites by identifying patterns and characteristics connected to phishing websites through a network training phase. …”
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8
An Intelligent Detection System for Rheumatoid Arthritis (RA) Disease using Image Processing
Published 2014“…In this research, First and Second Order Statistics Feature Extraction, Mamdani Fuzzy Logic Classification methods utilized to develop automatic detection system for RA with the help of Matlab R2012b, Fuzzy Logic Toolbox, and Image Processing Toolbox. …”
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9
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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10
P300 detection of brain signals using a combination of wavelet transform techniques
Published 2012“…In this research the BCI competition data-set has been processed through 5 optimized detection methods. Wavelet transform (WT), student’s two-sample t-statistic (T-Test) and support vector machines (SVM) used in designing the algorithms. …”
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11
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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12
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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13
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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14
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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15
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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16
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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17
Identifying melanoma characteristics using directional imaging algorithm and convolutional neural network on dermoscopic images / Mohammad Asaduzzaman Rasel
Published 2024“…Both phases of the research outputs are evaluated and compared with the state-of-the-art methods. The proposed algorithms that outperformed the state-of-the-art algorithms contributes to diagnosing early-stage Melanoma. …”
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18
Application Of Multi-Layer Perceptron Technique To Detect And Locate The Base Of A Young Corn Plant
Published 2007“…The recognition rate is presented and compared with another related research work, where the results show equal performance of both algorithms. This shows that machine-learning algorithm such as MLP is a viable method for color segmentation as well as object recognition.…”
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19
A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…Data mining is known as the process of detection concerning patterns from essential amounts of data. …”
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20
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…This study provides an improved control chart pattern recognition (CCPR) method focusing on X-bar chart patterns of small process variations using an ensemble classifier comprised of five complementing algorithms: decision tree, artificial neural network, linear support vector machine, Gaussian support vector machine, and k-nearest neighbours. …”
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