Search Results - (( emotion detection ((a algorithm) OR (_ algorithm)) ) OR ( wave optimisation system algorithm ))*
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Real-time system for facial emotion detection using GPSO algorithm
Published 2012Get full text
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Particle Swarm Optimization algorithm for facial emotion detection
Published 2010Get full text
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Facial emotion detection using GPSO and Lucas-Kanade algorithms
Published 2010Get full text
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Emotion Detection Based on EEG Signal
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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Final Year Project -
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Facial emotion detection using Guided Particle Swarm Optimization (GPSO)
Published 2009Get full text
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Effective EEG channels for emotion identification over the brain regions using differential evolution algorithm
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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Conference or Workshop Item -
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GPSO versus GA in facial emotion detection
Published 2012Subjects: “…Emotion detection…”
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Human Spontaneous Emotion Detection System
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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Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs
Published 2021“…The electroencephalogram (EEG) is a tool that potentially can be used to detect gender differences. …”
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Dyslexia handwriting detection using Convolutional Neural Network (CNN) algorithm / Sofea Najihah Mohd Zaki
Published 2024“…This project attempts to accurately detect the type of dyslexic handwriting. Convolutional Neural Network (CNN) algorithm was chosen as one of the possible solutions after a thorough analysis of many algorithms for dyslexic handwriting identification. …”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
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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Thesis -
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Detecting emotions and depression through voice
Published 2021“…A deep learning algorithm can detect emotion, including depression, using a voice signal. …”
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Affective computation on EEG correlates of emotion from musical and vocal stimuli
Published 2009“…A classification algorithm is subsequently used to learn and classify the extracted EEG features. …”
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Proceeding Paper -
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Enhanced emotion recognition in videos: a convolutional neural network strategy for human facial expression detection and classification
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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