Search Results - (( rate evaluation case algorithm ) OR ( pattern extraction method algorithm ))
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Adaptive Similarity Component Analysis in Nonparametric Dynamic Environment
Published 2011“…From a dimensionality reduction evaluation aspect, the average misclassification error of the proposed method in low-rank feature space is 9.6% and same error rate for three other well-known feature extraction methods is 21.21%. …”
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Thesis -
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Finger Vein Recognition Using Pattern Map As Feature Extraction
Published 2012“…This shows that pattern map is a reliable feature extraction method and is able to represent finger vein pattern effectively.…”
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Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier
Published 2018“…Classic local binary pattern (LBP) is one of the most useful feature extraction methods. …”
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Monograph -
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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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HEP-2 CELL IMAGES CLASSIFICATION BASED ON STATISTICAL TEXTURE ANALYSIS AND FUZZY LOGIC
Published 2014“…This project proposes a pattern recognition algorithm consisting of statistical methods to extract seven textural features from the HEp-2 cell images followed by classification of staining patterns by using fuzzy logic. …”
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Final Year Project -
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…As the components of big data continue to expand, the task of extracting useful information becomes critical. Topic extraction refers to the process of extracting main topics from the pool of news feed and a typical method to perform topic extraction is through clustering. …”
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Abnormal Pattern Detection In Ppg Signals Using Time Series Analysis
Published 2022“…This project’s objectives are to implement rule-based algorithm method for abnormal pattern detection in PPG signals, and to investigate the accuracy and performance of rule-based algorithm in detecting the abnormal pattern. …”
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Undergraduates Project Papers -
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Fingerprint verification using clonal selection algorithm / Farah Syadiyah Shamsudin
Published 2017“…Further studies can be made by using the same algorithm, but focusing more on the image enhancement and the feature extraction methods to improve the quality of the extraction of fingerprints.…”
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Thesis -
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…However, further study is needed in the feature extraction and clustering algorithms part as the performance of the pattern classification is still depending on the data input.…”
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Temporal - spatial recognizer for multi-label data
Published 2018“…Experiments on five datasets were conducted to compare the proposed method (imHTM) against statistical, template and structural pattern recognition methods. …”
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Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…As the components of big data continue to expand, the task of extracting useful information becomes critical. Topic extraction refers to the process of extracting main topics from the pool of news feed and a typical method to perform topic extraction is through clustering. …”
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Evaluation of a spacecraft attitude and rate estimation algorithm
Published 2010“…Purpose: This paper aims to present the development and performance evaluation of an attitude and rate estimation algorithm using an extended Kalman filter structure based on a body‐referenced representation of the state. …”
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Data mining using genetic algorithm in finance data / A. Noor Latiffah and A. B. Nordin
Published 2006“…The methods that wilt be applied are conventional statistical methods Markowitz Optimization as well as evolutionary programming (EP) utilizing genetic algorithms. …”
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Conference or Workshop Item -
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Neural Network Based Pattern Recognition in Visual Inspection System for Intergrated Circuit Mark Inspection
Published 1998“…Industrial visual machine inspection system uses template or feature matching methods to locate or inspect parts or pattern on parts. …”
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Pattern Recognition for Human Diseases Classification in Spectral Analysis
Published 2022“…Typically, pattern recognition consists of two components: exploratory data analysis and classification method. …”
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Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…An algorithm called Flex (Frequent lexicographic patterns) has been proposed in obtaining a good performance of searching li-equent patterns. …”
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Rough Neural Networks Architecture For Improving Generalization In Pattern Recognition
Published 2004“…The RNN was used to detect patterns present in satellite image. A novel feature extraction algorithm was developed to extract the feature vectors. …”
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Improved GART neural network model for pattern classification and rule extraction with application to power systems
Published 2023“…IGART enhances the dynamics of GART in several aspects, which include the use of the Laplacian likelihood function, a new vigilance function, a new match-tracking mechanism, an ordering algorithm for determining the sequence of training data, and a rule extraction capability to elicit if-then rules from the network. …”
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Fingerprint classification : a BI-resolution approach to singular point extraction
Published 2004“…This thesis presents a singular point extraction method using two layers of information, without pre-processing of the image. …”
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