Search Results - (( processes extraction method algorithm ) OR ( pattern classification methods algorithm ))
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…The problems in applying unsupervised learning/clustering is that this method requires teacher during the classification process and it has to learn independently which may lead to poor classification. …”
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Thesis -
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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Final Year Project -
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Finger Vein Recognition Using Pattern Map As Feature Extraction
Published 2012“…This shows that pattern map is a reliable feature extraction method and is able to represent finger vein pattern effectively.…”
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Thesis -
4
Fingerprint classification : a BI-resolution approach to singular point extraction
Published 2004“…This thesis presents a singular point extraction method using two layers of information, without pre-processing of the image. …”
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Herbs recognition based on chemical properties using machine learning algorithm
Published 2023“…This method has demonstrated promising results in identifying herb species, and the classification method based on machine learning algorithms has proven successful in recognizing and distinguishing herb species…”
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Article -
7
Development of a scaled conjugate gradient algorithm for significant RF neural signal processing
Published 2025“…Artificial Neural Networks (ANN) are computational models inspired by the human brain, capable of recognizing patterns and making predictions. Scale Conjugate Gradient (SCG) algorithm is an efficient training method for ANN that accelerates the learning process and improves output accuracy. …”
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EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter
Published 2019“…The process of developing the EEG eye state classification algorithm, includes data extraction, pre-processing, data normalization, feature extraction, feature selection and classification are detailed out in this paper. …”
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Conference or Workshop Item -
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EEG Eye State Identification based on Statistical Feature and Common Spatial Pattern Filter
Published 2019“…The process of developing the EEG eye state classification algorithm, includes data extraction, pre-processing, data normalization, feature extraction, feature selection and classification are detailed out in this paper. …”
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Conference or Workshop Item -
10
Biceps brachii surface EMG classification using neural networks
Published 2012“…The experimental results show that EMG signals of different biceps activity is differed and simple statistical features are sufficient to represent the EMG pattern. The proposed BPN with Levenberg-Marquardt (LM) algorithm and PNN had achieved an overall classification rate of 88% while BPN with Resilient-Propagation (RP) algorithm achieved an overall classification of 87.11%. …”
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Thesis -
11
Performance of Levenberg-Marquardt neural network algorithm in power quality disturbances classification / Adibah I’zzah Mohamad Kasim
Published 2025“…A simulation-based methodology was adopted, leveraging MATLABO/Simulink to model a power grid and generate synthetic PQD waveforms. The classification process incorporated Root Mean Square (RMS) analysis for feature extraction and multilayer perceptron (MLP) neural networks for pattern recognition. …”
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12
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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Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari
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Student Project -
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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…The increasing size of data being stored have created the need for computer-based methods for automatic data analysis. Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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Thesis -
15
A review on classifying and prioritizing user review-based software requirements
Published 2024“…This review revealed that leveraging opinion mining, sentiment analysis, natural language processing, or any stacking technique can significantly enhance the extraction and classification processes. …”
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Article -
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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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17
Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
Published 2018“…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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Thesis -
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A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…One of the outstanding classifications methods in data mining is support vector machine classification (SVM). …”
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Article -
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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals
Published 2020“…The first method is the Binary Tree Growth Algorithm (BTGA), which implements a hyperbolic tangent function to convert the Tree Growth Algorithm into the binary version. …”
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Thesis -
20
Hybrid multilayered perceptron network for classification of bundle branch blocks
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Working Paper
