Search Results - (( using application system algorithm ) OR ( pattern estimation using algorithm ))
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1
Fraud detection in telecommunication using pattern recognition method / Mohd Izhan Mohd Yusoff
Published 2014“…Due to the complexity of GMM, we use Expectation Maximization (or EM) algorithm by Dempster et al. (1977) to obtain the maximum likelihood estimates of the GMM parameters. …”
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Thesis -
2
Expectation maximization clustering algorithm for user modeling in web usage mining system
Published 2009“…In this study we advance a model for mining of user’s navigation pattern. The model is based on expectation-maximization (EM) algorithm and it is used for finding maximum likelihood estimates of parameters in probabilistic models, where the model depends on unobserved latent variables. …”
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Article -
3
Immune network algorithm in monthly streamflow prediction at Johor river
Published 2014“…The model of Immune Network Algorithm used in this study is aiNet. The training process in aiNet is partly inspired by clonal selection principle and the other part uses antibody interactions for removing redundancy and finding data patterns. …”
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Proceeding Paper -
4
Optimization of multipurpose reservoir operation using evolutionary algorithms / Mohammed Heydari
Published 2017“…An improved particle swarm algorithm (HPSOGA) is used to solve complex problems of water resources optimization. …”
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5
Stereo matching algorithm based on hybrid convolutional neural network and directional intensity difference
Published 2021“…A standard benchmarking evaluation system from the Middlebury Stereo dataset is used to measure the algorithm performance. …”
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6
Finger vein verification system using repeated line tracking and dimensionality reduction using PCA algorithms with SURF matching
Published 2017“…The Speeded-Up Robust Features (SURF) Algorithms is used to determine the interest points. …”
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Conference or Workshop Item -
7
Immune network algorithm in monthly streamflow prediction at Johor river
Published 2015“…The model of Immune Network Algorithm used in this study is aiNet. The training process in aiNet is partly inspired by clonal selection principle and the other part uses antibody interactions for removing redundancy and finding data patterns. …”
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Article -
8
Fingerprint classification : a BI-resolution approach to singular point extraction
Published 2004“…Two resolutions of the directional image are taken. The coarser level is used to estimate the position of singular points. …”
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Single-Port Beamforming Algorithm for 3-Faceted Phased Array Antenna
Published 2013“…In this letter, a novel single-port beamforming algorithm using the pseudo-inverse function is proposed. …”
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Conjunctions in biological neural architectures for visual pose estimation / Tom´As Maul
Published 2006“…As each level is traversed, a biological plausibility argument is gradually strengthened. At the algorithmic level, several approaches for solving the pose estimation problem are compared in terms of their neural implementability. …”
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12
Speech recognition system using MATLAB : design, implementation, and samples codes
Published 2011“…The most likely sequence is then decoded using Viterbi algorithm, thus producing the recognized word. …”
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Book -
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Apply and optimize machine learning algorithms for estimating battery health
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Final Year Project / Dissertation / Thesis -
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Spectral Estimation And Supervised Classification Technique For Real Time Electromyography Pattern Recognition
Published 2018“…Electromyography (EMG) signal is a biomedical signal which measures physical activity of human muscle.It has been acknowledged to be widely used in rehabilitation or recovery application system assisting physiotherapist to monitor a patient’s physical strength,function,motion and overall well-being by addressing the underlying physical issues.In application system associated with rehabilitation,a signal processing and classification techniques are implemented to classify EMG signal obtained.For real time application in the rehabilitation, the classification is crucial issue.The success of the signal classification depends on the selection of the features that represent a raw EMG signal in the signal processing.Therefore,a robust and resilient denoising method and spectral estimation technique have been acknowledged as necessary to distinguish and detect the EMG pattern.The present study was undertaken to determine the characteristic of EMG features using denoising method and spectral estimation technique for assessing the EMG pattern based on a supervised classification algorithm.In the study,the combination of time-frequency domain (TFD) and time domain (TD) were identified as the preferred denoising method and spectral estimation techniques.In the first part of study, the recorded EMG signal filtered the contaminated noise by using wavelet transform (WT) approach which implemented discrete wavelet transform (DWT) method of the wavelet-denoising signal. …”
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15
A COMBINED HISTOGRAM OF ORIENTED GRADIENTS AND COMPLETED LOCAL BINARY PATTERN METHODS FOR PEOPLE COUNTING IN A DENSE CROWD SCENARIO
Published 2016“…This method used a collaborative Histogram of Oriented Gradients (HOG) and Completed Local Binary Pattern (CLBP) based on people detection algorithm to detect headshoulder region. …”
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16
Monitoring and assessment of weld penetration condition during pulse mode laser welding using air-borne acoustic signal
Published 2021“…Among the monitoring systems in laser welding applications, acoustic methods have recently caught the attention of researchers due to their benefits in promoting simple, low-cost, and non-contact systems. …”
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DEVELOPMENT AND TESTING OF UNIVERSAL PRESSURE DROP MODELS IN PIPELINES USING ABDUCTIVE AND ARTIFICIAL NEURAL NETWORKS
Published 2011“…The ANN model has been developed using resilient back-propagation learning algorithm. …”
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All-in-1 adverse drug reaction reporting system / Long Chiau Ming … [et al.]
Published 2014“…Values obtained from this algorithm are used in peer reviews to verify the validity of reporter’s conclusion regarding ADRs. …”
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Book Section -
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Comparison of Stochastic Filtering Methods for 3D Tracking
Published 2011“…Kalman filter is a linear estimator which approximates system’s dynamics with Gaussian model while particle filter approximates system’s dynamics using weighted samples. …”
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