Search Results - (( feature classification parallel algorithm ) OR ( java implementation learning algorithm ))
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1
Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network
Published 2014“…Next, the classification was carried out. First, the best set of structures for feed forward neural network were found by multi objective parallel genetic algorithm. …”
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2
Intelligent classification algorithms in enhancing the performance of support vector machine
Published 2019“…Performing feature subset and tuning support vector machine (SVM) parameter processes in parallel with the aim to increase the classification accuracy is the current research direction in SVM. …”
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3
Image classification using two dimensional wavelet coefficients with parallel computing
Published 2020“…The low-level features such as edges, blobs, and ridges were extracted for grouping and classification. …”
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4
Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System
Published 2020“…The proposed method combined the improved teaching-learning-based optimisation (ITLBO) algorithm, improved parallel JAYA (IPJAYA) algorithm, and support vector machine. …”
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5
Combining deep and handcrafted image features for MRI brain scan classification
Published 2019“…In this paper, a deep learning feature extraction algorithm is proposed to extract the relevant features from MRI brain scans. …”
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6
Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm
Published 2008“…The prototype system, known as Java Plagiarism Detection System (JPDS) implements the Greedy-String-Tiling algorithm to detect similarities among tokens in a Java source code files. …”
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7
EMG motion pattern classification through design and optimization of neural network
Published 2012“…A back-propagation neural network with Levenberg-Marquardt training algorithm has been utilized for the classification of EMG signals. …”
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Proceeding Paper -
8
EMG motion pattern classification through design and optimization of Neural Network
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Working Paper -
9
Robust partitioning and indexing for iris biometric database based on local features
Published 2018“…The proposed method combines three transformation methods DCT, DWT and SVD to analyse iris images and extract their local features. Further, the scalable K-means++ algorithm is used for partitioning and classification processes, and an efficient parallel technique that divides the features groups causing the formation of two b-trees based on index keys is applied for search and retrieval. …”
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10
Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui
Published 2016“…Moreover, the proposed classifier technique is significantly faster than the recent well known methods, and it improves the efficiency by 71%, 3%, and 4% on feature extraction stage, feature reduction stage, and classification stage, respectively. …”
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11
Square patch feature based face detection architecture for high resolution smart camera
Published 2010“…From The simulation result shows that the proposed face detection architecture could speed up the equivalent software based face detector up to 12 times. Parallelizing the feature classification modules could improve the performance further.…”
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Proceeding Paper -
12
An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…Implemented with Java, this tool provides a friendly GUI for setting the parameters and display the result from where the learner can see how the selected algorithm converges for a particular problem solution. …”
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13
Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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14
A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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15
Recognizing complex human activities using hybrid feature selections based on an accelerometer sensor
Published 2017“…One of the limitations of the various classifications is to deal with the large dimension of the feature space. …”
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Article -
16
Hybrid harmony search-artificial intelligence models in credit scoring
Published 2019“…Then, the two types of features importance computed from RF algorithm are utilized for the attributes explanation. …”
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17
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…This project will use fuzzy k-means clustering algorithm to cluster the data because it is easy to implement and have many advantages. …”
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18
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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19
Electromygraphy (EMG) signal based hand gesture recognition using Artificial Neural Network (ANN)
Published 2011“…The EMG pattern signatures are extracted from the signals for each movement and then ANN utilized to classify the EMG signals based on features. A back-propagation (BP) network with Levenberg-Marquardt training algorithm has been used for the detection of gesture. …”
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Proceeding Paper -
20
On line fault detection for transmission line using power system stabilizer signals
Published 2007“…The same features are also fed to the Generalized Regression Neural Network (GRNN) and Probabilistic Neural Network (PNN) as a fault classifier and the results are compared for analyzing classification rate performance. …”
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