Search Results - (( pattern extraction method algorithm ) OR ( data reduction methods algorithm ))
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1
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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Thesis -
2
Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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3
Finger vein verification system using repeated line tracking and dimensionality reduction using PCA algorithms with SURF matching
Published 2017“…The feature vector of the vein pattern was then dimensionality reduction by Principal Component Analysis (PCA). …”
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4
Multispectral palm vein image fusion for contactless palm vein verification system
Published 2018“…SIFT algorithm achieved a reduction in EER rate by 12% in 700 nm, 8% in 850 nm, 7% in 940 nm compared with the SURF algorithm. …”
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5
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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6
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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7
P300 detection of brain signals using a combination of wavelet transform techniques
Published 2012“…Meanwhile the new approaches in channels selection methods help the algorithms for convenient online usage.…”
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8
Non-fiducial based ECG biometric authentication using one-class support vector machine
Published 2017“…This paper investigates the effect of different parameters of data set size, labeling data, configuration of training and testing data sets, feature extraction, different recording sessions, and random partition methods on accuracy and error rates of these SVM classifiers. …”
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9
Analysis of Traffic Accident Patterns Using Association Rule Mining
Published 2024“…This study also demonstrated the practicality of the apriori algorithm in analyzing extensive datasets to extract actionable insights. …”
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10
A new model for iris data set classification based on linear support vector machine parameter's optimization
Published 2020“…In this study, we proposed a newly mode for classifying iris data set using SVM classifier and genetic algorithm to optimize c and gamma parameters of linear SVM, in addition principle components analysis (PCA) algorithm was use for features reduction.…”
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11
Investigation of dimensionality reduction in a finger vein verification system
Published 2018“…The vein pattern was extracted using repeated line tracking and dimensionality reduction using principal components analysis to generate the feature vector. …”
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12
Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction
Published 2017“…A fitness function is proposed to deal with multi-objective problem without weight using a new composition method. The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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13
Fractal coding of bio-metric image for face authentication
Published 2021“…This thesis implements the algorithms for the Methods of CPM, BPBM fractal coding, and its application. …”
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14
Software agent as an effective tool for managing the Internet of thing data complexity
Published 2017“…Businesses have adopted certain algorithms that can help them to extract information from the Internet to discover potentially significant patterns inherent in the database, which can help the online marketing strategy. …”
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15
Channel selection for common spatial pattern Based on energy calculation of motor imagery EEG signal
Published 2017“…One of the popular features extraction methods for recognizing motor imagery EEG signal is Common Spatial Pattern (CSP). …”
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16
Prediction of Alzheimer disease using improved MMSE ensemble regressor based on magnetic resonance images
Published 2015“…Each hyperspace is assumed as perfect hyperspace if at least three of the regressors can predict perfectly all data pattern in it. Averaging method is adopted for predicting MMSE scores in any cluster. …”
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17
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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18
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 -
19
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 -
20
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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