Search Results - (( java applications using algorithm ) OR ( pattern classification means algorithm ))
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1
Pattern Classification of Human Epithelial Images
Published 2016“…Last but not least, from the mean of properties, it will classify into the pattern after ranging the value of mean properties of each of the pattern itself that has been done in classification stage.…”
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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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3
MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
Published 2011“…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
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4
MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
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5
Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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6
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 -
7
A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition
Published 2002“…That is, to use training speech patterns to generate classification rules that can be used later to classify input words patterns. …”
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8
Biceps brachii surface EMG classification using neural networks
Published 2012“…The experimental results show that EMG signals of different biceps activity is differed and simple statistical features are sufficient to represent the EMG pattern. The proposed BPN with Levenberg-Marquardt (LM) algorithm and PNN had achieved an overall classification rate of 88% while BPN with Resilient-Propagation (RP) algorithm achieved an overall classification of 87.11%. …”
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9
Acoustic echo cancellation using adaptive filtering algorithms for quranic accents (Qiraat) identification
Published 2015“…Based on our experimental results, the AP algorithm achieved 93.9 % accuracy rate against all pattern classification techniques including PPCA, KNN, and GMM. …”
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10
Frequent patterns minning of stock data using hybrid clustering association algorithm
Published 2009“…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data. …”
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Conference or Workshop Item -
11
Performance of Levenberg-Marquardt neural network algorithm in power quality disturbances classification / Adibah I’zzah Mohamad Kasim
Published 2025“…A simulation-based methodology was adopted, leveraging MATLABO/Simulink to model a power grid and generate synthetic PQD waveforms. 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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12
Acoustic echo cancellation using adaptive filter for Quranic accent signals
Published 2024“…AP indicates 93.9% for all of the classification algorithm in used, while for LMS and RLS the results are differed varies on different pattern classification algorithm stated whereby with LMS and PPCA classification, 96.9 % for accuracy and 84.8% accuracy for LMS and KNN. …”
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13
HEp-2 cell images classification based on statistical texture analysis and fuzzy logic
Published 2014“…The extracted features are then used as an input parameter to classify five staining patterns by using fuzzy logic. A working classification algorithm is developed and gives a mean accuracy of 84 out of 125 test images. …”
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14
Classification Of Hand Movements Based On Discrete Wavelet Transform And Enhanced Feature Extraction
Published 2019“…The EWL and EMAV are the modified version of wavelength (WL) and mean absolute value (MAV), which aims to enhance the prediction accuracy for the classification of hand movements. …”
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15
Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
Published 2018“…Subsequently,the filtered signal containing useful information was extracted by three methods root mean square (RMS),mean absolute value (MAV),and autoregressive (AR) covariance,all of which are commonly used in TD.A comparative analysis of the three different techniques was performed based on the accuracy performance of the EMG pattern classification using linear vector quantization (LVQ) neural network.In the experimental work undertaken,six healthy subjects comprised of males and females were selected. …”
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16
An improved multiple classifier combination scheme for pattern classification
Published 2015“…Combining multiple classifiers are considered as a new direction in the pattern recognition to improve classification performance. …”
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17
Ensemble Classifier for Recognition of Small Variation in X-Bar Control Chart Patterns
Published 2023“…The ensemble classifier can distinguish unstable pattern types with a classification accuracy of 99.55% and an ARL1 of 11.94.…”
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18
RSA Encryption & Decryption using JAVA
Published 2006“…References and theories to support the research of 'RSA Encryption/Decryption using Java' have been disclosed in Literature Review section. …”
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Final Year Project -
19
Geomorphometric analysis of landform pattern using topographic position and ASTER GDEM
Published 2017“…To quantify the spatial pattern of topographic position, Deviation from mean elevation (DEV) is adopted. …”
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20
Analysis And Classification Of Multiple Hand Gestures Using MMG Signals
Published 2018“…The main purpose of this work is to identify the hand gestures that are predefined using the artificial neural network,which is particularly useful for classification purpose.The MMG patterns are extracted from the signals for each movement,the features extracted from the signals are given to the neural network for training and classification since it is the good technique for classifying the bio signals.The features like mean absolute value,root mean square,variance,standard deviation and root mean square are chosen to train the neural network.…”
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