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1
Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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2
A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…That is, to use training speech patterns to generate classification rules that can be used later to classify input words patterns. …”
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Thesis -
3
Development of a new robust hybrid automata algorithm based on surface electromyography (SEMG) signal for instrumented wheelchair control
Published 2020“…Meanwhile, pattern recognition is using Probability Density Function (PDF) to determine MUAP according to type of activities. …”
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4
Correlation-based common spatial pattern (CCSP): A novel extension of CSP for classification of motor imagery signal
Published 2021“…Common spatial pattern (CSP) is shown to be an effective pre-processing algorithm in order to discriminate different classes of motor-based EEG signals by obtaining suitable spatial filters. …”
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5
Development of an intelligent system using Kernel-based learning methods for predicting oil-palm yield.
Published 2005“…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting oil-palm yield.…”
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6
Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
Published 2018“…Subsequently,the filtered signal containing useful information was extracted by three methods root mean square (RMS),mean absolute value (MAV),and autoregressive (AR) covariance,all of which are commonly used in TD.A comparative analysis of the three different techniques was performed based on the accuracy performance of the EMG pattern classification using linear vector quantization (LVQ) neural network.In the experimental work undertaken,six healthy subjects comprised of males and females were selected. …”
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7
A framework for predicting oil-palm yield from climate data
Published 2006“…The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data, and thus can be used for predicting oil-palm yield by analyzing various factors affecting the yield.…”
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Conference or Workshop Item -
8
A framework of modified adaptive neuro-fuzzy inference engine
Published 2012“…The Takagi-Sugeno-Kang (TSK) type fuzzy inference system was chosen and constructed by an automatic generation of clusters as well as membership functions and minimal rules through the use of hybrid fuzzy clustering and the modified apriori algorithms respectively. …”
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9
Firearm recognition based on whole firing pin impression image via backpropagation neural network
Published 2011“…A two-layer 6-7-5 connections BPNN of sigmoid/linear transfer functions with ‘trainlm’ algorithm was found to yield the best classification result using cross-validation, where 96% of the images were correctly classified according to the pistols used. …”
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Book Chapter -
10
Firearm recognition based on whole firing pin impression image via backpropagation neural network
Published 2011“…A two-layer 6-7-5 connections BPNN of sigmoid/linear transfer function with ‘trainlm’ algorithm was found to yield the best classification result using cross-validation, where 96% of the images were correctly classified according to the pistols used. …”
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Proceeding Paper -
11
Face emotion recognition using artificial intelligence techniques
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12
A study on component-based technology for development of complex bioinformatics software
Published 2004“…The second layer uses discriminative SVM algorithm with a state-of-the-art string kernel based on PSI-BLAST profiles that is used to leverage the unlabeled data. …”
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Monograph -
13
Comparative analysis for topic classification in juz Al-Baqarah
Published 2018“…The classification experiment is using the Support Vector Machine to find themes in Juz‟ Baqarah. …”
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14
Artificial neural network implementation on firearm recognition system with respect to ring firing pin impression image
Published 2011“…A two-layer 6-7-5 connections BPNN of sigmoid/sigmoid transfer functions with ‘trainscg’ algorithm was found to yield the best classification result using cross-validation, where 98% of the images were correctly classified according to the pistols used. …”
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Proceeding Paper -
15
Adaptive resonance theory-based hand movement classification for myoelectric control system
Published 2014“…Despite there has been a great development in prosthetic hand industry during the last decade, it is considerably needed to investigate an effective control algorithm for affordable prosthetic hand. This thesis investigates a pattern recognition approach for MCS that classifies hand movements accurately and computationally efficient to actuate different functions of a prosthetic hand. …”
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16
Development of drift conversion algorithm for ISFET based pH sensor for continuous measurement system
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Research Report -
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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18
Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier
Published 2018“…There are a lot of feature extraction methods and classification methods for iris classification. Classic local binary pattern (LBP) is one of the most useful feature extraction methods. …”
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Monograph -
19
Pattern Recognition for Human Diseases Classification in Spectral Analysis
Published 2022“…On the other hand, classification methods are techniques or algorithms used to group samples into a predetermined category. …”
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Article -
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