Search Results - (( a classification system algorithm ) OR ( pattern extraction method algorithm ))
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1
Realization Of The 1D Local Binary Pattern (LBP) Algorithm In Raspberry Pi For Iris Classification Using K-NN Classifier
Published 2018“…In this project, a classification system is proposed with the one-dimensional local binary pattern algorithm (1D-LBP) with the K-Nearest Neighbour (K-NN) classifier and the system is developed by using a Raspberry Pi 3.There are eight different subjects used to classify in this classification system and each subject consists of seven samples of normalized iris image as input to the system. …”
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Monograph -
2
Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…In pattern recognition system, achieving high accuracy in pattern classification is crucial. …”
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Thesis -
3
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 -
4
Improved GART neural network model for pattern classification and rule extraction with application to power systems
Published 2023“…In this paper, we propose an improved GART model (IGART), and demonstrate its applicability to power systems. 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. …”
Article -
5
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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6
Herbs recognition based on chemical properties using machine learning algorithm
Published 2023“…Innovatively, a new feature extraction method using the Weighted Histogram Analysis Method (WHAM) has been introduced. …”
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Article -
7
Biceps brachii surface EMG classification using neural networks
Published 2012“…The main rationale for the development of such a system is that the pattern of the EMG signals elicited may differ depending on the activity of the muscle movement. …”
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Thesis -
8
HEp-2 cell images classification based on statistical texture analysis and fuzzy logic
Published 2014“…This paper 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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Conference or Workshop Item -
9
Non-invasive pathological voice classifications using linear and non-linear classifiers
Published 2010“…It is concluded that proposed feature extraction and classification algorithms can be employed to help the medical professionals for early investigation of voice disorders.…”
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Thesis -
10
Performance of Levenberg-Marquardt neural network algorithm in power quality disturbances classification / Adibah I’zzah Mohamad Kasim
Published 2025“…The classification process incorporated Root Mean Square (RMS) analysis for feature extraction and multilayer perceptron (MLP) neural networks for pattern recognition. …”
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Thesis -
11
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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12
A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani
Published 2016“…The proposed algorithms have been tested on a variety of datasets from the UCI machine learning repository. …”
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13
A genetic algorithm based fuzzy inference system for pattern classification and rule extraction
Published 2023“…Setting fuzzy rules is one of the paramount techniques in the design of a fuzzy system. For a simple system, fuzzy if-then rules are usually derived from the human experts. …”
Article -
14
Development of a scaled conjugate gradient algorithm for significant RF neural signal processing
Published 2025“…Artificial Neural Networks (ANN) are computational models inspired by the human brain, capable of recognizing patterns and making predictions. Scale Conjugate Gradient (SCG) algorithm is an efficient training method for ANN that accelerates the learning process and improves output accuracy. …”
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Article -
15
Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari
Published 2018“…The main objective is to developing a classification system for agriculture plant by image pre-processing, feature extraction, network training and classification. …”
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Student Project -
16
Register Transfer Level Implementation Of Pooling - Based Feature Extraction For Finger Vein Identification
Published 2017“…The proposed algorithm extracted the local feature information of the finger vein pattern (patches), and used these patches to improve the robustness of the identification. …”
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17
Intelligent non-destructive classification of josapine pineapple maturity using artificial neural network
Published 2016“…Next, classification index to determine the pineapple maturity level has been applied which are linear classification using thresholding value and artificial neural network adopting pattern recognition method. …”
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18
APPLICATION OF LINK GRAMMAR IN SEMI-SUPERVISED NAMED ENTITY RECOGNITION FOR ACCIDENT DOMAIN
Published 2011“…The second contribution is the extraction pattern construction. Each named entity candidate will be assigned with an extraction pattern constructed from a set of word and syntactical feature. …”
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19
Hybrid multilayered perceptron network for classification of bundle branch blocks
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Working Paper -
20
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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Thesis
