Search Results - parallel estimation ((((learning algorithm) OR (sensor algorithm))) OR (path algorithm))*
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Image reconstruction using iterative transpose algorithm for optical tomography
Published 2007“…The measurement system consisted of two orthogonal arrays, each having ten parallel views, resulting in a total of twenty sensors. …”
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Simulated kalman filter (SKF) based image template matching for distance measurement by using stereo vision system
Published 2018“…Stereo vision sensor consists of two stereo cameras, mounted parallel in stationary position. …”
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Estimation of core size distribution of magnetic nanoparticles using high-Tc SQUID magnetometer and particle swarm optimizer-based inversion technique
Published 2023“…In this work, the core size estimation technique of magnetic nanoparticles (MNPs) using the static magnetization curve obtained from a high-Tc SQUID magnetometer and a metaheuristic inversion technique based on the Particle Swarm Optimizer (PSO) algorithm is presented. …”
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Magnetic resonance imaging sense reconstruction system using FPGA / Muhammad Faisal Siddiqui
Published 2016“…Parallel imaging is a robust method for accelerating the data acquisition in Magnetic Resonance Imaging (MRI). …”
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Super resolution imaging using modified lanr based on separable filtering
Published 2019“…The underlying idea is to process and reconstruct information in low and high frequency sub-bands based on separable property of neighbourhood filtering to achieve fast parallel and vectorized operation, while enhancing algorithmic performance by reducing computational burden resulting from computing the weighted function of every pixel for each pixel in an image. …”
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Short-term Gini coefficient estimation using nonlinear autoregressive multilayer perceptron model
Published 2024“…System Identification (SI), a methodology utilized in domains like engineering and mathematical modeling to construct or refine dynamic system models from captured data, relies significantly on the Nonlinear Auto-Regressive (NAR) model due to its reliability and capability of integrating nonlinear functions, complemented by contemporary machine learning strategies and computational algorithms to approximate complex system dynamics to address these limitations. …”
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