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  1. 1
    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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  2. 2
    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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  3. 3
    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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  4. 4
    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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  5. 5
    Lightning damage assessment on solar panels using in-house portable infrared thermography camera with Convolutional Neural Network (CNN) algorithm

    Lightning damage assessment on solar panels using in-house portable infrared thermography camera with Convolutional Neural Network (CNN) algorithm by Chandrasegaran, Ormiila, Mustapha, Faizal, Abdullah, Mohd Na’im, Anwar, Murniwati, Mustapha, Mazli, Adzis, Zuraimy

    Published 2024
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  6. 6
    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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  7. 7
    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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  8. 8
    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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  9. 9
    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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  10. 10
    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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  11. 11
    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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  12. 12
    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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  13. 13
    Beyond Sentiment Analysis: A Review of Recent Trends in Text Based Sentiment Analysis and Emotion Detection

    Beyond Sentiment Analysis: A Review of Recent Trends in Text Based Sentiment Analysis and Emotion Detection by Lai Po Hung, Suraya Alias

    Published 2023
    “…So besides writer sentiments, writer emotion is also a valuable data. Emotion detection can be done using text, facial expressions, verbal communications and brain waves; however, the focus of this review is on text-based sentiment analysis and emotion detection. …”
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  14. 14
    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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  15. 15
    Effective EEG channels for emotion identification over the brain regions using differential evolution algorithm

    Effective EEG channels for emotion identification over the brain regions using differential evolution algorithm by Al-Qazzaz, Noor Kamal, Sabir, Mohannad K., Md. Ali, Sawal Hamid, Ahmad, Siti Anom, Grammer, Karl

    Published 2019
    “…Furthermore, the right and left occipital channels may help in identifying happiness, sadness, surprise and neutral emotional states. The DEFS_Ch algorithm raised the linear discriminant analysis (LDA) classification accuracy from 80% to 86.85%, indicating that DEFS_Ch may offer a useful way for reliable enhancement of the detection of different emotional states of the brain regions.…”
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  16. 16
    Enhanced emotion recognition in videos: a convolutional neural network strategy for human facial expression detection and classification

    Enhanced emotion recognition in videos: a convolutional neural network strategy for human facial expression detection and classification by Ashraf, Arselan, Gunawan, Teddy Surya, Arifin, Fatchul, Kartiwi, Mira, Sophian, Ali, Habaebi, Mohamed Hadi

    Published 2023
    “…To address these issues, we propose a comprehensive CNN-based model for real-time detection and classification of five primary emotions: anger, happiness, neutrality, sadness, and surprise. …”
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  17. 17
    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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  18. 18
    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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  19. 19
    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
    “…The objectives of this research are to classify the user emotion characteristics by using EEG signals based on children’s behaviour, to develop a prototype of an emotion prediction system named as MYEmotion and to validate the developed prototype in predicting the positive and negative emotions of the children. 16 datasets of attention and meditation levels were collected from a qualitative sampling of 10 years old school children in Pekan, Pahang using a BCI headset tool. …”
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  20. 20
    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 enhancement is in particular relative in emotional memory. Stress become a serious issues nowadays. …”
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