Search Results - (( using estimation method algorithm ) OR ( motion optimization method algorithm ))*
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…Block Matching Algorithm (BMA) is a technique used to minimize the computational complexity of motion estimation in video coding application. …”
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Thesis -
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Multilevel optimization for dense motion estimation
Published 2011“…We evaluated the performance of different optimization techniques developed in the context of optical flow computation with different variational models.In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we developed the use of efficient multilevel schemes for computing the optical flow.More precisely, we evaluated the performance of a standard unidirectional multilevel algorithm - called multiresolution optimization (MR/Opt), to a bidrectional multilevel algorithm - called full multigrid optimization (FMG/Opt).The FMG/Opt algorithm treats the coarse grid correction as an optimization search direction and eventually scales it using a line search. …”
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…Block-matching algorithm is the most common technique applied in block-based motion estimation technique. …”
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Book Chapter -
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Algorithm optimization and low cost bit-serial architecture design for integer-pixel and sub-pixel motion estimation in H.264/AVC / Mohammad Reza Hosseiny Fatemi
Published 2012“…This thesis is concerned with algorithm optimization and efficient low cost architecture design for integer motion estimation (IME) and sub-pixel motion estimation (SME) of H.264/AVC. …”
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SLOW DRIFT MOTIONS IDENTIFICATION OF FLOATING STRUCTURES USING TIME-VARYING INPUT -OUTPUT MODELS
Published 2015“…The first step is presenting the backward estimator and combined forward-backward estimator instead of the only forward estimator in the original input-output models; the second step is reformulating the input-output models into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the model coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) and Artificial Bee Colony (ABC) to form the PSO-KS, GA-KS and ABC-KS as estimation methods.…”
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Parameter estimation of stochastic differential equation
Published 2012“…The results showed that the Mean Square Errors (MSE) for stochastic model with parameters estimated using optimal knot for 1,000, 5,000 and 10,000 runs of Brownian motions are smaller than the SDE models with estimated parameters using knot selected heuristically. …”
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A comprehensive analysis of surface electromyography for control of lower limb exoskeleton
Published 2016“…Initial estimate of the model is obtained from literature review while the Levenderg-Marquardt (LM) method is applied to solve the nonlinear least squares optimization problem. …”
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The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…The implementation of pre-processing algorithms has been demonstrated to be able to mitigate the signal noises that arises from the winking signals without the need for the use signal filtering algorithms. …”
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Minimizing machining airtime motion with an ant colony algorithm
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A Metaheuristic Optimization Using Explosion Method On A Hybrid Pd2-Lqr Quadcopter Controller
Published 2021“…Therefore, an optimization algorithm based on the explosion method called REA was proposed and implemented on the proposed Hybrid PD2-LQR control structure. …”
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Application of sampling-based motion planning algorithms in autonomous vehicle navigation
Published 2016“…The proposed method provides near-optimal solutions with smaller trees and in lower running time.…”
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