Search Results - data distribution ((function algorithm) OR (((recognition algorithm) OR (conversion algorithm))))
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Enhancing clustering algorithm with initial centroids in tool wear region recognition
Published 2020“…K-means clustering has become the most applied algorithm in discovering classes in an unsupervised scenario. …”
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A Divide-and-Distribute Approach to Single-Cycle Learning HGN Network for Pattern Recognition
Published 2010“…Distributed Hierarchical Graph Neuron (DHGN) is a single-cycle learning distributed pattern recognition algorithm, which reduces the computational complexity of existing pattern recognition algorithms by distributing the recognition process into smaller clusters. …”
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Distributed Video Tracking
Published 2018“…In this project, we will come out with an effective way surveillance and monitoring through algorithm for video tracking. There are three main phases for the algorithm for video tracking: object recognition, data transmission, object tracking. …”
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Final Year Project -
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Temporal - spatial recognizer for multi-label data
Published 2018“…Hence, there is a need for a recognition algorithm that can separate the overlapping data points in order to recognize the correct pattern. …”
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Embedded vision system development using 32-bit Single Board Computer and GNU/Linux
Published 2011“…The overall software design is divided into three modules which are Image Acquisition, Image Processing and Object Detection, and Data Transmission module. The image processing algorithm includes color space conversion and motion analysis technique. …”
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Thesis -
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Hierarchical Bayesian estimation for stationary autoregressive models using reversible jump MCMC algorithm
Published 2018“…In the hierarchical Bayesian approach, the order and coefficients of the autoregressive model are assumed to have a prior distribution. The prior distribution is combined with the likelihood function to obtain a posterior distribution. …”
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Parallel guided image processing model for ficus deltoidea (Jack) moraceae varietal recognition
Published 2018“…Nowadays, with the huge number of leaves data, plant species recognition process becomes computationally expensive. …”
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Book Section -
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…Thereafter, a multi-objective hybrid algorithm (MOHA), an extension of the self-adaptive hybrid algorithm is proposed and tested on the established multi-objective (MO) test functions. …”
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Thesis -
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Class binarization with self-adaptive algorithm to improve human activity recognition
Published 2018“…Furthermore, although better recognition of stairs activities is accomplished, recognition of stationary activities is less reported due to less sensitivity of lesser waveform. …”
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Thesis -
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A new Gompertz-three-parameter-lindley distribution for modeling survival time data
Published 2025“…The statistical properties of the proposed distribution including the shape properties, cumulative distribution, quantile functions, moment generating function, failure rate function, mean residual function, and stochastic orders are studied. …”
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Reliability Analysis and Prediction of Time to Failure Distribution of an Automobile Crankshaft
Published 2015“…The developed stochastic algorithm has the capability to measure the parametric distribution function and validate the predict the reliability rate, mean time to failure and hazard rate. …”
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Semiparametric inference procedure for the accelarated failure time model with interval-censored data
Published 2019“…The main contribution of this research is developing statistical approaches, and introducing new algorithms and resampling methods for analysing interval-censored data through AFT models.…”
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Thesis -
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Slice sampler algorithm for generalized pareto distribution
Published 2018“…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
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Parallel algorithms for numerical simulations of EHD ion-drag micropump on distributed parallel computing systems
Published 2014“…In order to evaluate the scalability at specific data size the appropriate regression models are fitted through the measured data as functions of number of workers. …”
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Thesis -
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Parameter-driven count time series models / Nawwal Ahmad Bukhari
Published 2018“…A key property of our model is that the distributions of the observed count data are independent, conditional on the latent process, although the observations are correlated marginally. …”
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Thesis -
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Malay continuous speech recognition using continuous density hidden Markov model
Published 2007“…With their efficient training algorithm (Baum-Welch and Viterbi/Segmental K-mean) and recognition algorithm (Viterbi), as well as it’s modeling flexibility in model topology, observation probability distribution, representation of speech unit and other knowledge sources, HMM has been successfully applied in solving various tasks in this thesis. …”
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Sizing and placement of solar photovoltaic plants by using time-series historical weather data
Published 2018“…To predict the output from the PV modules, 15 years of solar data were modeled with the aid of a beta probability density function. …”
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