Search Results - (( emotion detection system algorithm ) OR ( based verification system algorithm ))
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Speech emotion verification system (SEVS) based on MFCC for real time applications
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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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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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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Secured Autonomous Agent-Based Intrusion Detection System (SAAIDS)
Published 2024thesis::master thesis -
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Integration Of Fingerprint Centre Point Location And Principal Component Analysis For Fingerprint Verification
Published 2005“…Principal Component Analysis (Pca) Is Utilized In This System. The Proposed Cp Estimation Algorithm Is Based On The Alteration Tracking (At) Followed By An Estimation Algorithm. …”
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Facial emotion detection using Guided Particle Swarm Optimization (GPSO)
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Stress Level Detection using Fuzzy Logic / Nor Husna Nabila Khuzaini
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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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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Intelligent biometric signature verification system incorporating neural network
Published 2005“…An intelligent feature of the system is made possible through the application of a multilayer feedforward neural network that is used together with suitable algorithms to complement the verification process. …”
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Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin
Published 2017“…Therefore, the aim for this project is to develop a new approach in the fingerprint verification system by applying Clonal Selection Algorithm (CSA) that is known to be good in pattern matching and optimization of problems. …”
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Stroke-to-stroke matching in on-line signature verification
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