Search Results - (( emotion detection ((a algorithm) OR (_ algorithm)) ) OR ( based presentation based algorithm ))
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Particle Swarm Optimization algorithm for facial emotion detection
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Facial emotion detection using Guided Particle Swarm Optimization (GPSO)
Published 2009Get full text
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Vader lexicon and support vector machine algorithm to detect customer sentiment orientation
Published 2023“…To accomplish this, a dataset from the Amazon website will be analyzed and classified using the Support Vector Machine algorithm. …”
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Development of Image-Based Emotion Recognition using Convolutional Neural Networks
Published 2021“…One of the prominent applications is detecting emotion from an image, which can help an intelligent automatic response system respond appropriately based on the user’s emotion. …”
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Proceeding Paper -
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Intelligent humanoid emotion response based on human emotion recognition for virtual intercommunication simulator
Published 2023“…The research delves into fundamental human emotions, computational emotion models, face detection algorithms, and fuzzy logic inference systems. …”
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Conference or Workshop Item -
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Eye fixation versus pupil diameter as eye- tracking features for virtual reality emotion classification
Published 2022“…We classified emotions into four distinct classes according to Russell’s four-quadrant Circumplex Model of Affect. 3600 videos are presented as emotional stimuli to participants in a VR environment to evoke the user’s emotions. …”
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Proceedings -
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Characterization of digital intra-oral dental radiographs based on image enhancement algorithms (IEAs) / Siti Arpah Ahmad
Published 2017“…The final lists of images with abnormalities are presented as a new abnormality matrix in table form, to characterize the intra-oral dental radiographs abnormalities. …”
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Thesis -
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Real-time system for facial emotion detection using GPSO algorithm
Published 2012Get 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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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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Deep learning model for 5W (What, When, Where, Who, and Why) sign language translation system / Raihah Aminuddin, Ummu Mardhiah Abdul Jalil and Norsyamimi Hasran
Published 2023“…This ensures that other people can understand the message the hearing-impaired person is trying to convey. This research presents a 5W sign language identification system based on the Convolutional Neural Network technique and the You Only Look Once algorithm. …”
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