Search Results - (( motion optimization method algorithm ) OR ( simulation optimization matching algorithm ))
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Image Template Matching Based on Simulated Kalman Filter (SKF) Algorithm
Published 2018“…A novel approach to the image matching based on Simulated Kalman Filter (SKF) algorithm has been proposed in this paper. …”
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Illumination-Invariant Image Matching Based on Simulated Kalman Filter (SKF) Algorithm
Published 2018“…In order, the traditional algorithm to solve image matching problem take a lot of memory and computational time, image matching problem is assigned to optimization problem and can be solve precisely. …”
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Application of Evolutionary Algorithm for Assisted History Matching
Published 2014“…Besides, it really demands skill and experience on the part of simulation engineer. Today, tremendous efforts are made to develop Automatic History Matching algorithms. …”
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Final Year Project -
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…In addition, it is expected that it can be applied in real-time application. In this study, Simulated Kalman Filter (SKF) is applied to image template matching application as the optimization algorithm. …”
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Hexagon pattern particle swarm optimization based block matching algorithm for motion estimation / Siti Eshah Che Osman
Published 2019“…Recently, intelligent searching methods were proposed to enhance the computational optimization issues in motion estimation but still lack in obtaining the best solution of block matching. …”
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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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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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Monograph -
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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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Book Section -
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Artificial neural network and inverse solution method for assisted history matching of a reservoir model
Published 2017“…This allows to directly simulate the trained neural network and avoid the use of objective function and optimization algorithm. …”
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Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching
Published 2014“…History matching is a process of altering parameters in a reservoir simulator in order to match production performance with observed historical data. …”
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Final Year Project