Search Results - pattern extraction means algorithm*
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Pattern Discovery Using K-Means Algorithm
Published 2024“…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”
Proceedings Paper -
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Pattern discovery using k-means algorithm
Published 2014“…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”
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Modeling of vehicle trajectory clustering based on LCSS for traffic pattern extraction
Published 2017“…The implementation of k-means and fuzzy c-means (FCM) clustering algorithm for vehicle flow analyzing task is served as focus in this paper. …”
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Proceedings -
4
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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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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Final Year Project -
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Automatic document clustering and indexing of multiple documents using KNMF for feature extraction through Hadoop and lucene on big data
Published 2023“…Automatic indexing; Big data; Cluster analysis; Extraction; Factorization; Indexing (of information); Information retrieval; K-means clustering; Natural language processing systems; Open source software; Open systems; Pattern matching; Software quality; Software testing; Text mining; Hadoop; Key phrase extractions; Map-reduce; Pattern-matching technique; Porters; Pre-processing algorithms; Software environments; Unlabeled; Matrix algebra…”
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Near infrared palm image acquisition and two-finger valley point-based image extraction for palm vascular pattern detection
Published 2019“…The biometric recognition process was done by extraction of vascular line features by Local Binary Pattern (LBP), and classification by K-nearest neighbour (KNN) algorithm using cross-validation technique. …”
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Thesis -
9
Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Although effective, the performance of the k-means clustering algorithm depends heavily on the initial centroids and the number of clusters, k. …”
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Modeling of vehicle trajectory using K-means and fuzzy C-means clustering
Published 2019“…Hence, the clustering of vehicle trajectory dataset for similar patterns identification is implemented with k-means and fuzzy c-means (FCM) clustering algorithm. …”
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Proceedings -
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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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Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering
Published 2021“…In the field of computer science, data mining facilitates the extraction of useful knowledge and patterns from a huge amount of data. …”
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13
Social media mining: a genetic based multiobjective clustering approach to topic modelling
Published 2021“…Although effective, the performance of the k-means clustering algorithm depends heavily on the initial centroids and the number of clusters, k. …”
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Biceps brachii surface EMG classification using neural networks
Published 2012“…After preprocessing, the signal is passed to the feature extraction module. In this module, statistical features such as mean, maximum, variance and standard deviation are computed to represent the signal pattern. …”
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Thesis -
15
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 -
16
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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Classification Of Hand Movements Based On Discrete Wavelet Transform And Enhanced Feature Extraction
Published 2019“…The extracted features are then fed into the machine learning algorithm for classification process. …”
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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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Thesis -
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Urban green space spatio-temporal change influences on land surface temperature in Kuala Lumpur, Malaysia
Published 2020“…The study also applied land surface emissivity (LSE) algorithm to determine the LST value extracted from the Band 10 parameter of Landsat 8 OLI/TIRS. …”
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20
Electromyography signal processing based on time and time-frequency representations for prosthesis application
Published 2014“…To reach this goal, different techniques in two domains of study, time and time-frequency, had been utilized to find the optimum features for EMG analysis. Mean Absolute Value (MAV), Root Mean Square (RMS), Zero Crossing (ZC) and Waveform Length (WL) were employed as feature extraction techniques in time domain and Wavelet Transform (WT) was used in time-frequency domain. …”
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