Search Results - (( gender classification based algorithm ) OR ( java application sensor algorithm ))
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Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network
Published 2020“…Thus, this paper proposed metaheuristic algorithms such as Particle Swarm Optimization, Ant Colony Algorithm and Harmony Search Algorithm based feature selection to identify the most significant features of skeleton remains. …”
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Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs
Published 2021“…Finally, the k-nearest neighbors ( kNN) classification technique was used for automatic gender identification of an emotional-based EEG dataset. …”
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A study of frequency radiation of human torso for gender classification
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Multilayer Perceptron Neural Network In Classifying Gender Using Fingerprint Global Level Features
Published 2016“…Background/Objective: A new algorithms of gender classification from fingerprint is proposed based on Acree 25mm2 square area. …”
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Multilanguage speech-based gender classification using time-frequency features and SVM classifier
Published 2021“…The classification is done based on features derived from the frequency and time domain processing using the Support Vector Machines (SVM) algorithm. …”
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First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms
Published 2014“…The comparative analysis is also conducted to discover the best classification model for prediction. From the experiment, the models develop using Rule Based and Decision Tree algorithm shows the best result compared to the model develop from the Naïve Bayes algorithm. …”
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Development of Low Cost Heart Rate Monitoring Device and Classification Technique Using Fuzzy Logics Algorithm
Published 2016“…The classification of the signal being obtained is achieved through fuzzy logics algorithm inside the MATLAB Fuzzy Logic Toolbox. …”
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Final Year Project -
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Classification Of Gender Using Global Level Features In Fingerprint For Malaysian Population
Published 2016“…A new approach of algorithm based on the Mark Acree’s theory, focusing on fingerprint global extracted features is proposed and implemented for enhancing gender classification method. …”
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Gender Classification: A Convolutional Neural Network Approach
Published 2016“…An approach using a convolutional neural network (CNN) is proposed for real-time gender classification based on facial images. The proposed CNN architecture exhibits a much reduced design complexity when compared with other CNN solutions applied in pattern recognition. …”
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Making programmer effective for software development teams: An extended study
Published 2017“…Basically, two types of decision rules were formed: rules without gender classification of programmer but they only discussed the personality types of team-leader and programmer. …”
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Human body radiation wave analysis and classification for gender and body segments recognition / Siti Zura A. Jalil @ Zainuddin
Published 2014“…Multivariate analysis of variance (MANOVA) is employed to compare the differences of frequency radiation characteristics between genders. Then, the classification algorithm of A:-nearest neighbor (KNN) is employed to discriminate between genders, and between body segments. …”
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data
Published 2014“…Therefore, the work presented here includes embedded hardware system that works with classification algorithm on real EEG signals, in a ubiquitous setting. …”
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Embedded Fuzzy Classifier for Detection and Classification of Preseizure state using Real EEG data
Published 2014“…Therefore, the work presented here includes embedded hardware system that works with classification algorithm on real EEG signals, in a ubiquitous setting. …”
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Book Section -
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An enhancement of age and gender classification accuracy with hybrid handcrafted and deep features using hierarchical extreme learning machine / Mohammad Javidan Darugar
Published 2020“…Age and gender classification are some of the essential algorithms that have many use cases in our everyday life. …”
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Embedded Fuzzy Classifier for Detection and Classification of Preseizure State Using Real EEG Data
Published 2013“…Therefore, the work presented here includes embedded hardware system that works with classification algorithm on real EEG signals, in a ubiquitous setting. …”
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Early autism spectrum disorder detection using machine learning / Muhammad Shahmi Shahron Nizan
Published 2023“…This project aims to develop a web-based application utilizing the Random Forest Classification Algorithm to aid concerned parents in detecting potential Autism Spectrum Disorder (ASD) symptoms in their children aged 1-6 years in Malaysia. …”
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Speaker identification through feature fusion based deep learning / Rashid Jahangir
Published 2021“…In addition, DNN obtained better classification results compared with the other five machine learning algorithms that were recently utilised in speaker recognition. …”
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Finding an effective classification technique to develop a software team composition model
Published 2017“…Ineffective software team composition has become recognized as a prominent aspect of software project failures.Reports from results extracted from different theoretical personality models have produced contradicting fits, validity challenges, and missing guidance during software development personnel selection.It is also believed that the technique/s used while developing a model can impact the overall results.Thus, this study aims to: 1) discover an effective classification technique to solve the problem, and 2) develop a model for composition of the software development team.The model developed was composed of three predictors: team role, personality types, and gender variables; it also contained one outcome: team performance variable.The techniques used for model development were logistic regression, decision tree, and Rough Sets Theory (RST).Higher prediction accuracy and reduced patte rn complexity were the two parameters forselecting the effective technique.Based on the results, the Johnson Algorithm (JA) of RST appeared to be an effective technique for a team composition model.The study has proposed a set of 24 decision rules for finding effective team members.These rules involve gender classification to highlight the appropriate personality profile for software developers.In the end, this study concludes that selecting an appropriate classification technique is one of the most important factors in developing effective models.…”
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