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Biometrics: Facial Recognition
Published 2004“…It also lists the various approaches in handling facial recognition where we see different methods applied and opinions on which method is better and what factors influenced them. …”
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Final Year Project -
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Artifact identification for blood pressure and photoplethysmography signals in an unsupervised environment / Lim Pooi Khoon
Published 2020“…Upon using the artifact detection method followed by BP estimation, the SBP and DBP were improved in BHS grades from D to A. …”
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Thesis -
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Multichannel optimization with hybrid spectral- entropy markers for gender identification enhancement of emotional-based EEGs
Published 2021“…Finally, the k-nearest neighbors ( kNN) classification technique was used for automatic gender identification of an emotional-based EEG dataset. …”
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Feature extraction using spectral centroid and mel frequency cepstral coefficient for Quranic accent automatic identification
Published 2014“…This paper presents the process of Quranic Accent Automatic Identification. Recent feature extraction technique that is used for Quranic verse rule identification/Tajweed include Mel Frequency Cepstral Coefficients (MFCC) which prone to additive noise and may reduce the classification result. …”
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Conference or Workshop Item -
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A multi-color based features from facial images for automatic ethnicity identification model
Published 2019“…Finally, the proposed ethnicity identification was tested using several classification algorithms. …”
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Crypt Edge Detection Using PSO,Label Matrix And BI-Cubic Interpolation For Better Iris Recognition(PSOLB)
Published 2017“…Recently,there has been renewed interest in iris features detection.Gabor filter,cross entrophy, upport vector,and canny edge detection are methods which produce iris codes in binary codes representation.However,problems have occurred in iris recognition since low quality iris images are created due to blurriness,indoor or outdoor settings, and camera specifications.Failure was detected in 21% of the intra-class comparisons cases which were taken between intervals of three and six months intervals.However,the mismatch or False Rejection Rate (FRR) in iris recognition is still alarmingly high.Higher FRR also causes the value of Equal Error Rate (EER) to be high.The main reason for high values of FRR and EER is that there are changes in the iris due to the amount of light entering into the iris that changes the size of the unique features in the iris.One of the solutions to this problem is by finding any technique or algorithm to automatically detect the unique features.Therefore a new model is introduced which is called Crypt Edge Detection which combines PSO,Label Matrix,and Bi-Cubic Interpolation for Iris Recognition (PSOLB) to solve the problem of detection in iris features.In this research, the unique feature known as crypts has been chosen due to its accessibility and sustainability.Feature detection is performed using particle swarm optimisation (PSO) as an algorithm to select the best iris texture among the unique iris features by finding the pixel values according to the range of selected features.Meanwhile, label matrix will detect the edge of the crypt and the bi-cubic interpolation technique creates sharp and refined crypt images.In order to evaluate the proposed approach,FAR and FRR are measured using Chinese Academy of Sciences' Institute of Automation (CASIA) database for high quality images.For CASIA version 3 image databases, the crypt feature shows that the result of FRR is 21.83% and FAR is 78.17%.The finding from the experiment indicates that by using the PSOLB,the intersection between FAR and FRR produces the Equal Error Rate (EER) with 0.28%,which indicated that equal error rate is lower than previous value, which is 0.38%.Thus,there are advantages from using PSOLB as it has the ability to adapt with unique iris features and use information in iris template features to determine the user.The outcome of this new approach is to reduce the EER rates since lower EER rates can produce accurate detection of unique features.In conclusion,the contribution of PSOLB brings an innovation to the extraction process in the biometric technology and is beneficial to the communities.…”
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Thesis -
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Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification
Published 2020“…In this research, a fully automated system is presented to automatically detect the various states of the epileptic seizure. …”
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Article -
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System Identification And Control Of Automatic Car Pedal Pressing System For Low-Speed Driving In A Road Traffic Delay
Published 2022“…Both controllers were then implemented and tested in automatic car pedal pressing system. The controller gains were tuned using metaheuristic algorithm which is Particle Swarm Algorithm (PSO) for optimal values of fuzzy controller parameters. …”
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Undergraduates Project Papers -
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Smart Cards And The Fingerprint : A Proposed Framework For The Automatic Teller Machine (ATM) System
Published 2002“…As a result, the research proposed a framework for user identification and authentication in automatic teller machine (ATM) systems using fingerprints and smart cards as opposed to the PIN and magnetic-stripe cards. …”
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Thesis -
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Analysis of minutia extraction techniques in fingerprint recognition.
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Working Paper -
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Fault identification in pipeline system using normalized hilbert huang transform and automatic selection of intrinsic mode function
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Online fingerprint recognition
Published 2010“…Fingerprints are the most popularly used in biometric identification and recognition systems, because they can be easily used and their features are highly reliable. …”
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Undergraduates Project Papers -
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The efficacy of deep learning algorithm in classifying chilli plant growth stages
Published 2021“…The demand in this field has created various opportunities, especially for automatic classification using deep learning methods. …”
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Automatic clustering of generalized regression neural network by similarity index based fuzzy c-means clustering
Published 2004“…This algorithm offers better performance than conventional algorithm which using energy only. …”
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