Search Results - (( motion estimation tree algorithm ) OR ( based optimization isotherm algorithm ))
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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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Evaluating the effects of the dual tree complex wavelet transform and the adaptive rood pattern search algorithm on a video codec
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IMPACT OF NUMBER OF ATTRIBUTES ON THE ACCURACY OF HUMAN MOTION CLASSIFICATION
Published 2018“…Present studies merely focus on estimating joints, skeleton and motions of human activities. …”
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A gauss-newton approach for nonlinear optimal control problem with model-reality differences
Published 2017“…Here, the linear model-based optimal control model is considered, so as the optimal control law is constructed. …”
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Multi-sensor fusion based on multiple classifier systems for human activity identification
Published 2019“…The study proposes a multi-view ensemble algorithm to integrate predicted values of different motion sensors. …”
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Production and characterization of biochar derived from oil palm wastes, and optimization for zinc adsorption
Published 2015“…The incremental back propagation algorithm demonstrated the best results and which has been used as learning algorithm for ANN in combination with Genetic Algorithm in the optimization. …”
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Modeling of Cu(II) adsorption from an aqueous solution using an Artificial Neural Network (ANN)
Published 2020“…The Fletcher-Reeves conjugate gradient backpropagation (BP) algorithm was the best fit among all of the tested algorithms (mean squared error (MSE) of 3.84 and R2 of 0.989). …”
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Modelling and simulation of hollow profile aluminium extruded product
Published 2015“…This process is an isothermal process with an extrusion ratio of 3.3. Subsequently, the optimized algorithm for these extrusion parameters was suggested based on the simulation results. …”
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Modeling of cu(ii) adsorption from an aqueous solution using an artificial neural network (ann)
Published 2020“…The Fletcher–Reeves conjugate gradient backpropagation (BP) algorithm was the best fit among all of the tested algorithms (mean squared error (MSE) of 3.84 and R2 of 0.989). …”
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