Search Results - (( process classification methods algorithm ) OR ( pattern classification system algorithm ))

Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition by Leong, Shi Xiang

“…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis by Jantan, Hamidah, Drahman, Fatimatul Zahrah, Alhadi, Nazirah, Mamat, Fatimah

“…Machine learning approach such as immune system based learning methods is an alternative way for sentiment classification.This method is centered on prominent immunological theory as computation mechanisms that emulate processes in biological immune system in achieving higher probability for pattern recognition. …”
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Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

“…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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HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC by Jamil, Nur Farahim

“…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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Biceps brachii surface EMG classification using neural networks by Chong, Yee Lin

“…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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Development of a scaled conjugate gradient algorithm for significant RF neural signal processing by Mohd Norden, Muhammad Farid Akmal, Mohd Isa, Roshakimah, Mohd Isa, Mohd Roshalizi, S. Abdul Kadir, Ros Shilawani, Md Azli, Muhammad Hariz, Muhammad Akram, Amir Syarif

“…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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Individual And Ensemble Pattern Classification Models Using Enhanced Fuzzy Min-Max Neural Networks by F. M., Mohammed

“…Pattern classification is one of the major components for the design and development of a computerized pattern recognition system. …”
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Performance of Levenberg-Marquardt neural network algorithm in power quality disturbances classification / Adibah I’zzah Mohamad Kasim by Mohamad Kasim, Adibah I’zzah

“…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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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification by Loo, C.K., Liew, W.S., Sayeed, M.S.

“…This study is an attempt to design a method for an autonomous pattern classification and recognition system for emotion recognition. …”
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Fingerprint classification : a BI-resolution approach to singular point extraction by Leong, Chung Ern

“…This thesis presents a singular point extraction method using two layers of information, without pre-processing of the image. …”
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Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari by Sha’ari, Nor Silawati

“…NN such as Artificial Neural Network (ANN) and K-Nearest Neighbor (KNN) is trained in developing a classification system for agriculture purpose. ANN and KNN is applied to solve the problems in image analysis, pattern recognition and classification. …”
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Herbs recognition based on chemical properties using machine learning algorithm by Mohamad Radzi, Nur Fadzilah, Che Soh, Azura, Ishak, Asnor Juraiza, Hassan, Mohd Khair

“…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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A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

“…One of these tools is Artificial Immune Recognition System (AIRS), which has been used increasingly. Results of AIRS have shown its potential for classification purposes. …”
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A New Probabilistic Output Constrained Optimization Extreme Learning Machine by Wong S.Y., Yap K.S., Li X.C.

“…Benchmarking; Classification (of information); Constrained optimization; Decision making; Electric power systems; Iterative methods; Knowledge acquisition; Learning algorithms; Pattern recognition; Probability; Confidence threshold; Decision making process; Extreme learning machine; Machine learning approaches; Pattern classification problems; Post-processing procedure; Power system applications; Probabilistic output; Machine learning…”

Intelligent non-destructive classification of josapine pineapple maturity using artificial neural network by Nazriyah, Haji Che Zan @ Che Zain

“…The results show that the classification using artificial neural network (pattern recognition) involving feature vectors arithmetic average and standard deviation for all channels R, G and B give the average correct classification rate of 88.89%.…”
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Hybrid multilayered perceptron network for classification of bundle branch blocks by Megat Syahirul Amin, Megat Ali, Ahmad Nasrul, Norali, Aisyah Hartini, Jahidin

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Design Of Feature Selection Methods For Hand Movement Classification Based On Electromyography Signals by Too, Jing Wei

“…Therefore, this thesis aims to solve the feature selection problem in EMG signals classification and improve the classification performance of EMG pattern recognition system. …”
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition by Burhan, Nuradebah

“…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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A performance comparison study of pattern recognition systems for volatile organic compounds detection / Emilia Noorsal, Muhammad Khusairi Osman and Norfadzilah Mokhtar by Noorsal, Emilia, Osman, Muhammad Khusairi, Mokhtar, Norfadzilah

“…The performance of each neural network was analysed in terms of the classification accuracy, average score, total training time required during the training process and the test time of the optimised networks. …”
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Classification of chest radiographs using novel anomalous saliency map and deep convolutional neural network by Md. Ali, Mohd. Adli, Abidin, Mohd Radhwan, Nik Muhamad Affendi, Nik Arsyad, Abdullah, Hafidzul, Rosman, Daaniyal Reesha, Badrud'din, Nu'man, Kemi, Faiz, Hayati, Farid

“…The rapid advancement in pattern recognition via the deep learning method has made it possible to develop an autonomous medical image classification system. …”
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