Blar i NTNU Open på forfatter "Necoara, Ion"
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Accelerating support vector machines for remote platforms by increasing sparsity
Garrett, Joseph; Singh, N; Johansen, Tor Arne; Necoara, Ion (Peer reviewed; Journal article, 2022)The support vector machine (SVM) classification algorithm often achieves quite high accuracy on hyperspectral images, even when trained on small amounts of data. However, SVMs can still be computationally expensive relative ... -
Dimensionality reduction of hyperspectral images using an ICA-based stochastic second-order optimization algorithm
Lupu, Daniela; Necoara, Ion; Ionescu, Tudor C.; Ghinea, L M; Garrett, Joseph Landon; Johansen, Tor Arne (Chapter, 2023)Hyperspectral imaging is one of the advanced remote sensing techniques whose goal is to obtain the spectrum for each pixel in the image of a scene, with the purpose of finding objects, identifying materials or detecting ... -
Efficient Implementation of Dual First Order Algorithms - Application in Embedded MPC
Kvamme, Sverre (Master thesis, 2014)In this Thesis, numerical implementation of optimization algorithms for convex quadratic problems that appear in model predictive control for embedded linear systems, are examined. Different versions of dual first order ... -
Stochastic Higher-Order Independent Component Analysis for Hyperspectral Dimensionality Reduction
Lupu, Daniela; Necoara, Ion; Garrett, Joseph Landon; Johansen, Tor Arne (Peer reviewed; Journal article, 2022)Hyperspectral imaging is a remote sensing technique that measures the spectrum of each pixel in the image of a scene. Various methods have been developed to reduce the spectral dimension of hyperspectral images in order ...