Search Results - (( using vector error algorithm ) OR ( pattern classification using algorithm ))
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1
Incremental continuous ant colony optimization for tuning support vector machine’s parameters
Published 2013“…Support Vector Machines are considered to be excellent patterns classification techniques. …”
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2
Optimizing support vector machine parameters using continuous ant colony optimization
Published 2012“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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3
Formulating new enhanced pattern classification algorithms based on ACO-SVM
Published 2013“…This paper presents two algorithms that integrate new Ant Colony Optimization (ACO) variants which are Incremental Continuous Ant Colony Optimization (IACOR) and Incremental Mixed Variable Ant Colony Optimization (IACOMV) with Support Vector Machine (SVM) to enhance the performance of SVM.The first algorithm aims to solve SVM model selection problem. …”
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Content adaptive fast motion estimation based on spatio-temporal homogeneity analysis and motion classification
Published 2012“…This is the basis of the proposed algorithm. The proposed algorithm involves a multistage approach that includes motion vector prediction and motion classification using the characteristics of video sequences. …”
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Intelligent non-destructive classification of josapine pineapple maturity using artificial neural network
Published 2016“…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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Thesis -
6
Analysis Of Failure In Offline English Alphabet Recognition With Data Mining Approach
Published 2019“…Classification analysis was initially performed on all seven classifier’s algorithms at 10-fold dross validation mode. …”
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Monograph -
7
Non-fiducial based ECG biometric authentication using one-class support vector machine
Published 2017“…The personal identity verification in a random population using kernel-based binary and one-class Support Vector Machines (SVMs) has been considered by other biometric traits, but has been so far left aside for analysis of ECG signals. …”
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A new classifier based on combination of genetic programming and support vector machine in solving imbalanced classification problem
Published 2016“…There are two methods in dealing with imbalanced classification problem, which are based on data or algorithmic level. …”
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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
Published 2007“…The types of VOCs used for the classification were Acetone, Benzene, Chloroform, Ethanol and Methanol. …”
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Research Reports -
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Classification Of Gender Using Global Level Features In Fingerprint For Malaysian Population
Published 2016“…Two classification approaches which are the descriptive statistical and data mining are used in order to examine the classification of the gender by using the five extracted features. …”
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12
Apply and optimize machine learning algorithms for estimating battery health
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Final Year Project / Dissertation / Thesis -
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Feature extraction and classification stage on facial expression : A review
Published 2022“…Lastly, the optimization technique for image classification using a three-staged Support Vector Machine (SVM) is very helpful for increasing accuracy and eliminating error. …”
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Conference or Workshop Item -
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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 -
15
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 -
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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 -
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Condition monitoring of deep drilling process for cooling channel making in hot press die
Published 2016“…SVM performs classification process based on the data input vector that comprise as fault in the machine. …”
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Undergraduates Project Papers -
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Comparative analysis of spatio/spectro-temporal data modelling techniques
Published 2017“…Other challenges include the dynamic pattern of spatial components features and inconsistency in the number of samples and feature-length used in the training and sampling datasets [2]. …”
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Book Section -
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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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Thesis -
20
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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