Search Results - (( gender classification using algorithm ) OR ( java implication tree algorithm ))

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    Gender classification on skeletal remains: efficiency of metaheuristic algorithm method and optimized back propagation neural network by Hairuddin, Nurul Liyana, Yusuf, Lizawati Mi, Othman, Mohd Shahizan

    Published 2020
    “…This was to obtain a good combination of parameters in order to produce a better gender classification. This study used 1,538 data samples from Goldman Osteometric Dataset which consisted of femur, humerus and tibia parts. …”
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    Article
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    Multilayer Perceptron Neural Network In Classifying Gender Using Fingerprint Global Level Features by Siti Fairuz, Abdullah, Ahmad Fadzli Nizam, Abdul Rahman, Zuraida, Abal Abas, Wira Hidayat, Mohd Saad

    Published 2016
    “…Background/Objective: A new algorithms of gender classification from fingerprint is proposed based on Acree 25mm2 square area. …”
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    Article
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    Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs by Al-Qazzaz, Noor Kamal, Sabir, Mohannad K., Mohd Ali, Sawal Hamid, Ahmad, Siti Anom, Grammer, Karl

    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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    Article
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    Classification Of Gender Using Global Level Features In Fingerprint For Malaysian Population by Abdullah, Siti Fairuz

    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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    Thesis
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    Multilanguage speech-based gender classification using time-frequency features and SVM classifier by Wani, Taiba, Gunawan, Teddy Surya, Mansor, Hasmah, Ahmad Qadri, Syed Asif, Sophian, Ali, Ambikairajah, Eliathamby, Ihsanto, Eko

    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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    Book Chapter
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    Gender identification using support vector machines by Nur Ayuni Binti Jalaluddin

    Published 2023
    “…This research study discusses about the gender identification and it is using support vector machines to meet the objective. …”
    text::Thesis
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    First Semester Computer Science Students’ Academic Performances Analysis by Using Data Mining Classification Algorithms by Azwa, Abdul Aziz, Fadhilah, Ahmad

    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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    Conference or Workshop Item
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    Development of Low Cost Heart Rate Monitoring Device and Classification Technique Using Fuzzy Logics Algorithm by Faili, Zahra

    Published 2016
    “…This would let end users (physicians/Caregivers) to have a real-time heart rate monitoring without a need of connecting wires from the patient ward/room to the remote station which was designed in MATLAB GUI. 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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    Human body radiation wave analysis and classification for gender and body segments recognition / Siti Zura A. Jalil @ Zainuddin by A. Jalil @ Zainuddin, Siti Zura

    Published 2015
    “…Multivariate analysis of variance (MANOVA) is employed to compare the differences of frequency radiation characteristics between genders. Then, the classification algorithm of k-nearest neighbor (KNN) is employed to discriminate between genders, and between body segments. …”
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    Book Section
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    Gender Classification: A Convolutional Neural Network Approach by Shan, Sung Liew, Mohamed, Khalil-Hani, Syafeeza, Ahmad Radzi, Rabia, Bakhteri

    Published 2016
    “…An approach using a convolutional neural network (CNN) is proposed for real-time gender classification based on facial images. …”
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    Article
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    Human body radiation wave analysis and classification for gender and body segments recognition / Siti Zura A. Jalil @ Zainuddin by A. Jalil @ Zainuddin, Siti Zura

    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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    Thesis
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    Embedded fuzzy classifier for detection and classification of preseizure state using real EEG data by Qidwai, U., Malik, A.S., Shakir, M.

    Published 2014
    “…The algorithm also utilizes certain statistical features from the EEG signal that are used as features to the classifier logic. …”
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    Conference or Workshop Item
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    Embedded Fuzzy Classifier for Detection and Classification of Preseizure state using Real EEG data by Qidwai, Uvais, Malik, Aamir Saeed, Shakir, Mohamed

    Published 2014
    “…The algorithm also utilizes certain statistical features from the EEG signal that are used as features to the classifier logic. …”
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    Book Section
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    Development of Malay word pronunciation application using vowel recognition by Mohd Yusof, Shahrul Azmi

    Published 2016
    “…In Malaysia, many researchers focus on developing speaker independent systems for training or articulation therapy or to assist language learners to learn about Malay Language or Bahasa Malaysia.Accuracy, noise robustness and processing time are concerns when developing speech therapy systems.In this study, a Malay word pronunciation test application was developed using the first 3 format and fundamental frequencies in an effort to improve pronunciation in Malay.This application was developed using Matlab and uses a vowel recognition algorithm classified using MLP classification technique.The application was developed and tested on UUM undergraduate students.For vowel classification, when fundamental frequency was added, 3-format feature vowel classification rate increased by 1.55% for male gender and 1.48% for female. …”
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    Article
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    Embedded Fuzzy Classifier for Detection and Classification of Preseizure State Using Real EEG Data by Qidwai, Uvais, Malik, Aamir Saeed, Shakir, Mohamed

    Published 2013
    “…The algorithm also utilizes certain statistical features from the EEG signal that are used as features to the classifier logic. …”
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    Book Section
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    Finding an effective classification technique to develop a software team composition model by Gilal, Abdul Rehman, Jaafar, Jafreezal, Capretz, Luiz Fernando, Omar, Mazni, Basri, Shuib, Abdul Aziz, Izzatdin

    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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    Article