Search Results - (( java application testing algorithm ) OR ( based emotion based algorithm ))

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  1. 1
    Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs

    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
    “…Investigating gender differences based on emotional changes supports automatic interpretation of human intentions and preferences. …”
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  2. 2
    RSA Encryption & Decryption using JAVA

    RSA Encryption & Decryption using JAVA by Ramli, Marliyana

    Published 2006
    “…The implementation of this project will be based on Rapid Application Design Methodology (RAD) and will be more focusing on research and finding, ideas and the implementation of the algorithm, and finally running and testing the algorithm. …”
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  3. 3
    An Algorithm to Define Emotions Based on Facial Gestures as Automated Input in Survey Instrument

    An Algorithm to Define Emotions Based on Facial Gestures as Automated Input in Survey Instrument by Tayib, Saifulazmi, Jamaludin, Zulikha

    Published 2016
    “…Features of facial gestures that play important role in creating emotions are selected to be formulated in the algorithm.The aim of this paper is to produce an algorithm to define emotions based on three facial features namely mouth, eyes, and eyebrows.This is done by studying users and the problem domain, analyzing the relationship between emotions and facial gestures, and formulating solutions to the problem.This algorithm will be useful in developing a more interactive survey instrument and improving user interaction between researchers and dyslexic children.…”
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  4. 4
    Deep learning based emotion recognition for image and video signals: matlab implementation

    Deep learning based emotion recognition for image and video signals: matlab implementation by Ashraf, Arselan, Gunawan, Teddy Surya, Kartiwi, Mira

    Published 2021
    “…Five emotions are considered for recognition: angry, happy, neutral, sad, and surprise, compared to previous algorithms. …”
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  5. 5
    Emotion recognition and analysis of netizens based on micro-blog during covid-19 epidemic

    Emotion recognition and analysis of netizens based on micro-blog during covid-19 epidemic by Jiao, BianBian, Leelavathi, R., Lohgheswary, N., Nopiah, Z. M.

    Published 2022
    “…The research is about emotion recognition and analysis based on Micro-blog short text. …”
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  6. 6
    EEG-based emotion recognition using machine learning algorithms

    EEG-based emotion recognition using machine learning algorithms by Lam, Yee Wei

    Published 2024
    “…Human emotions are very complex and hard to identify based on their facial expressions and appearance. …”
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    Final Year Project / Dissertation / Thesis
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  7. 7
    Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion

    Fuzzy clustering for genetic algorithm based optimized ellipse data in classifying face emotion by Muthukaruppan, Karthigayan, Mohd Rizon, Mohamed Juhari, Sazali, Yaacob, Ramachandran, Nagarajan, Masanori, Sugisaka, Mohd Rozailan, Mamat

    Published 2009
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  8. 8
    Emotion Detection Based on EEG Signal

    Emotion Detection Based on EEG Signal by Mohamad Nasaruddin, Noradila

    Published 2021
    “…Thus, this project aimed to study the emotion detection through EEG signal and proposed the right algorithm to process the signal. …”
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  9. 9
    An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition

    An enhanced computational model based on social spider optimisation algorithm for EEG- based emotion recognition by Al-Qammaz, Abdullah Yousef Awwad

    Published 2019
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  10. 10
    Development of a personified face emotion recognition technique using fitness function

    Development of a personified face emotion recognition technique using fitness function by Muthukaruppan, Karthigayan, Mohd Rizon, Mohamed Juhari, Ramachandran, Nagarajan, Masanori, Sugisaka, Sazali, Yaacob, Mohd Rozailan, Mamat, Hazry, Desa

    Published 2009
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  11. 11
    Personalized human emotion classification using genetic algorithm

    Personalized human emotion classification using genetic algorithm by Mohd Rizon, Hazry, Desa, Karthigayan, M., Nagarajan, Ramachandran, Alajlan, N., Sazali, Yaacob, Prof. Dr., Nor Azmi, Johari, Ina Suryani, Ab Rahim

    Published 2010
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  12. 12
    Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition

    Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition by Al-Qammaz, Abdullah Yousef, Ahmad, Farzana Kabir, Yusof, Yuhanis

    Published 2018
    “…Due to some limitations of current heuristics and evolutionary algorithms, this paper proposed a new swarm based algorithm for feature selection method called Social Spider Optimization (SSO-FS). …”
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  13. 13
    Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application

    Comparison of Search Algorithms in Javanese-Indonesian Dictionary Application by Yana Aditia, Gerhana, Nur, Lukman, Arief Fatchul, Huda, Cecep Nurul, Alam, Undang, Syaripudin, Devi, Novitasari

    Published 2020
    “…Performance Testing is used to test the performance of algorithm implementations in applications. …”
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  14. 14
    Particle Swarm Optimization algorithm for facial emotion detection

    Particle Swarm Optimization algorithm for facial emotion detection by Ghandi, B.M., Nagarajan, R., Hazry, Desa, Prof. Madya Dr.

    Published 2010
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  15. 15
    Speech emotion verification system (SEVS) based on MFCC for real time applications

    Speech emotion verification system (SEVS) based on MFCC for real time applications by Kamaruddin, Norhaslinda, Abdul Rahman, Abdul Wahab

    Published 2008
    “…Since features extracted using the MFCC simulates the function of the human cochlea, neural network (NN) and fuzzy neural network algorithm namely; Multi Layer Perceptron (MLP), Adaptive Network-based Fuzzy Inference System (ANFIS) and Generic Selforganizing Fuzzy Neural Network (GenSoFNN) were used to verify the different emotions. …”
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  16. 16
    Predicting game-induced emotions using EEG, data mining and machine learning

    Predicting game-induced emotions using EEG, data mining and machine learning by Min, Xuan Lim, Jason Teo

    Published 2024
    “…The 20 experiment cases’ results from subject-based experiments supported that the SVM classifer could accurately classify the 4 emotion states with a kappa value over 0.62, demonstrating the SVM-based algorithm’s capabilities in precisely determining the emotion label for each participant’s EEG features’ instance. …”
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  17. 17
    A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering

    A Parallel-Model Speech Emotion Recognition Network Based on Feature Clustering by Li-Min Zhang, Giap Weng Ng, Yu-Beng Leau, Hao Yan

    Published 2023
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  18. 18
    A parallel-model speech emotion recognition network based on feature clustering

    A parallel-model speech emotion recognition network based on feature clustering by Li-Min Zhang, Giap Weng Ng, Yu-Beng Leau, Hao Yan

    Published 2023
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  19. 19
    Determinism in speech pitch relation to emotion

    Determinism in speech pitch relation to emotion by Ahmed Mustafa Mahmoud, *, Wan, Haslina Hassan*

    Published 2009
    “…In this paper, a deterministic approach to emotional speech rule-based synthesis algorithm is presented. …”
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  20. 20
    Discrete wavelet packet transform for electroencephalogram based valence-arousal emotion recognition

    Discrete wavelet packet transform for electroencephalogram based valence-arousal emotion recognition by Olakunle, Oyenuga Wasiu

    Published 2015
    “…The aim of this study is to discover the feature extraction method and the combination of electrode channels that optimally implements EEG-based valencearousal emotion recognition. Based on this, two emotion recognition experiments were performed to classify human emotional states into high/low valence or high/low arousal. …”
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