Search Results - (( emotional detection system algorithm ) OR ( based optimization _ algorithm ))*

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  1. 1
    GPSO versus GA in facial emotion detection

    GPSO versus GA in facial emotion detection by Bashir, Mohammed Ghandi, Ramachandran, Nagarajan, Prof. Dr., Sazali, Yaacob, Prof. Dr., Hazry, Desa, Assoc. Prof. Dr.

    Published 2012
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  2. 2
    Facial emotion detection using Guided Particle Swarm Optimization (GPSO)

    Facial emotion detection using Guided Particle Swarm Optimization (GPSO) by Bashir, Mohammed Ghandi, Nagarajan, R., Hazry, Desa

    Published 2009
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  3. 3
    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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  4. 4
    Facial geometry and speech analysis for depression detection

    Facial geometry and speech analysis for depression detection by Pampouchidou, A., Simantiraki, O., Vazakopoulou, C.-M., Chatzaki, C., Pediaditis, M., Maridaki, A., Marias, K., Simos, P., Yang, F., Meriaudeau, F., Tsiknakis, M.

    Published 2017
    “…Optimal system performance was obtained using a nearest neighbour classifier on the decision fusion of geometrical features in the gender independent mode, and audio based features in the gender based mode; single visual and audio decisions were combined with the OR binary operation. © 2017 IEEE.…”
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  5. 5
    Real-time system for facial emotion detection using GPSO algorithm

    Real-time system for facial emotion detection using GPSO algorithm by Bashir, Mohammed Ghandi, R., Nagarajan, Prof. Dr., Hazry, Desa, Assoc. Prof. Dr.

    Published 2012
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  6. 6
    Facial emotion detection using GPSO and Lucas-Kanade algorithms

    Facial emotion detection using GPSO and Lucas-Kanade algorithms by Bashir, Mohammed Ghandi, Nagarajan, Ramachandran, Prof. Dr., Hazry, Desa, Prof. Madya Dr.

    Published 2010
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  7. 7
    Human Spontaneous Emotion Detection System

    Human Spontaneous Emotion Detection System by Radin Monawir, Radin Puteri Hazimah

    Published 2018
    “…Having smart computerized system which can understand and instantly gives appropriate response to human is the utmost motive in human and computer interaction (HCI) field.It is argued either HCI is considered advance if human could not have natural and comfortable interaction like human to human interaction.Besides,despite of several studies regarding emotion detection system, current system mostly tested in laboratory environment and using mimic emotion.Realizing the current system research lack of real life or genuine emotion input,this research work comes up with the idea of developing a system that able to recognize human emotion through facial expression.Therefore,the aims of this study are threefold which are to enhance the algorithm to detect spontaneous emotion,to develop spontaneous facial expression database and to verify the algorithm performance.This project used Matlab programming language,specifically Viola Jones method for features tracking and extraction,then pattern matching for emotion classification purpose.Mouth feature is used as main features to identify the emotion of the expression.For verification purpose,the mimic and spontaneous database which are obtained from internet,open source database or novel (own) developed databases are used.Basically,the performance of the system is indicated by emotion detection rate and average execution time.At the end of this study,it is found that this system is suitable for recognizing spontaneous facial expression (63.28%) compared to posed facial expression (51.46%).The verification even better for positive emotion with 71.02% detection rate compared to 48.09% for negative emotion detection rate.Finally,overall detection rate of 61.20% is considered good since this system can execute result within 3s and use spontaneous input data which known as highly susceptible to noise.…”
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  8. 8
    Emotion detecting humanoid – the use of GPSO Algorithm

    Emotion detecting humanoid – the use of GPSO Algorithm by Bashir, Mohammed Ghandi, Ramachandran, Nagarajan, Prof. Dr., Hazry, Desa, Assoc. Prof. Dr.

    Published 2012
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  9. 9
    Various Recognition approach in human faces

    Various Recognition approach in human faces by Karthigayan, M., Mohd Rizon, Mohamed Juhari, Sazali, Yaacob, Nagarajan, R., Puteh, Saad, Muhammed Firdaus, Hashim, Haniza, Yazid

    Published 2009
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  10. 10
    Human faces: a review from detection to recognition

    Human faces: a review from detection to recognition by Mohamed Rizon, Mohamed Juhari, Muthukaruppan, Karthigayan, Sazali, Yaacob, Ramachandran, Nagarajan, Puteh, Saad, P. L. EhKan

    Published 2009
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  11. 11
    A Simple Yet Reliable Facial Emotion Detection For Campus Environment

    A Simple Yet Reliable Facial Emotion Detection For Campus Environment by Amar Lokman, Mus’ab Sahrim, Wan Zakiah Wan Ismail, Sharma Rao Balakrishnan, Juliza Jamaludin

    Published 2024
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  12. 12
    Stress Level Detection using Fuzzy Logic / Nor Husna Nabila Khuzaini

    Stress Level Detection using Fuzzy Logic / Nor Husna Nabila Khuzaini by Khuzaini, Nor Husna Nabila

    Published 2020
    “…This fuzzy logic system were successful develop. The result indicate in stress level detection based on fuzzy logic system that provide the symptom of stress and the facial emotion. …”
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  13. 13
    HelpMe: early detection of university students' mental health issues using a chatbot-integrated dashboard / Nadia Abdul Wahab ... [et al.]

    HelpMe: early detection of university students' mental health issues using a chatbot-integrated dashboard / Nadia Abdul Wahab ... [et al.] by Nadia Abdul Wahab, Nadia Abdul Wahab, Ahmad Asyraf Zainudin, Ahmad Asyraf Zainudin, Norfiza Ibrahim, Norfiza Ibrahim, Aznoora Osman, Aznoora Osman, Abdul Hapes Mohammed, Abdul Hapes Mohammed

    Published 2025
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  14. 14
    Detecting emotions and depression through voice

    Detecting emotions and depression through voice by Gunawan, Teddy Surya

    Published 2021
    “…A deep learning algorithm can detect emotion, including depression, using a voice signal. …”
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  15. 15
    Detection of mental disorders based on the analysis of emotion, facial expressions and facial movements in a video stream

    Detection of mental disorders based on the analysis of emotion, facial expressions and facial movements in a video stream by Nurzhanova, Aizhan, Mussabek, Miras, Ince, Gokhan, Mustaffa, Mas Rina, Zhumadillayeva, Ainur

    Published 2025
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  16. 16
    Multiview face emotion recognition using geometrical and texture features

    Multiview face emotion recognition using geometrical and texture features by Goodarzi, Farhad

    Published 2017
    “…A 3D face pose estimation algorithm detects head rotations of Yaw, Roll and Pitch for emotion recognition. …”
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  17. 17
    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool

    Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool by Nurshafiqa Saffah, Mohd Sharif

    Published 2018
    “…In future, this research can be an initial work in automating tutorial decisions in an intelligent tutoring system which are able to adapt to the behaviour of the learners based on the detected mental states. …”
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  18. 18
    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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  19. 19
    Human emotion classifications for automotive driver using skin conductance response signal

    Human emotion classifications for automotive driver using skin conductance response signal by Minhad, Khairun Nisa', Md. Ali, Sawal Hamid, Ooi, Jonathan Shi Khai, Ahmad, Siti Anom

    Published 2016
    “…Risky driving is an attitude associated with human states of emotion. Emotions detected using facial and body movements, sounds and physiological changes which required multiple and bulky instruments such as camera, voice recorder and sensors. …”
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  20. 20
    The design for antrophomorphic sociable agent interaction through emotion detection

    The design for antrophomorphic sociable agent interaction through emotion detection by Ab. Aziz, Azizi, Siraj, Fadzilah, Sainin, Mohd Shamrie, Mohd Hassin, Mohd Hafiz

    Published 2003
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