Search Results - (( emotion detection method algorithm ) OR ( _ classification system algorithm ))*
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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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Facial expression type recognition using K-Nearest Neighbor algorithm / Norhafizah Saffian
Published 2017“…Customer satisfaction measurement is one of the most crucial ways to identify and improve the business strategy of the organization and the department that involved is in the customer service management. One of the methods to measure the customer satisfaction is by trying to measure the customer emotional aspect. …”
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Learner’s emotion prediction using production rules classification algorithm through brain computer interface tool
Published 2018“…From the data analysis using WEKA software, the production rules classifier (PART) is found to be the most accurate classification algorithm in classifying the emotion which yields the highest precision percentage of 99.6% compared to J48 (99.5%) and Naïve Bayes (96.2%). …”
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Human emotion classifications for automotive driver using skin conductance response signal
Published 2016“…The video clip stimulus method showed 95.7% efficacy in detecting happiness and anger. …”
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Vader lexicon and support vector machine algorithm to detect customer sentiment orientation
Published 2023“…Additionally, the study showcases the novelty and superiority of the annotation process used for detecting customer orientation classifications. Methods: This study employs a method to compare the classification performance of the Vader lexicon annotation process with manual annotation. …”
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Face expression recognition using artificial neural network (ANN) / Mazuraini Ghani
Published 2005“…This project is all about implementing the back-propagation neural network algorithm in classification of face expression. This project has 3 objectives. …”
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Facial geometry and speech analysis for depression detection
Published 2017“…The algorithms were evaluated for several combinations of parameters and classification schemes, on the dataset provided by the Audio/Visual Emotion Challenge of 2013 and 2014. …”
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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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Beyond Sentiment Analysis: A Review of Recent Trends in Text Based Sentiment Analysis and Emotion Detection
Published 2023“…Perhaps the next task to catch on is emotion detection, the task of identifying emotions. …”
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Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs
Published 2021“…Therefore, the proposed methods were effective in improving the process of automatic gender recognition from the emotional-based EEG signals.…”
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Dengue classification system using clonal selection algorithm / Karimah Mohd
Published 2012“…This project focused on three main objectives: to investigate dengue data and Clonal Selection Algorithm for classification of Dengue, to design and develops Clonal Selection Classification System (CSCS) and to evaluate Clonal Selection Classification System symptoms. …”
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Multiview face emotion recognition using geometrical and texture features
Published 2017“…A 3D face pose estimation algorithm detects head rotations of Yaw, Roll and Pitch for emotion recognition. …”
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An enhancement of classification technique based on rough set theory for intrusion detection system application
Published 2019“…In order to improve classification performance problem, feature selection and discretization algorithm are crucial in selecting relevant attributes that could improve classification performance. …”
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Phylogenetic tree classification system using machine learning algorithm
Published 2015“…A study is conducted to develop an automated phylogenetic tree image classification system by using machine learning algorithm. …”
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Final Year Project Report / IMRAD -
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Algorithms for moderating effect of emotional value from a cross-media data fusion perspective: a case study of Chinese dating reality shows
Published 2026“…This research demonstrates a new algorithmic method of moderating emotional content within Chinese dating reality shows based on cross-media analysis, combining text, audio, video, and social media feedback. …”
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Face detection in image sequence / Noor Diana Abdullah
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