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Publikováno v:
Applied optics. 60(25)
In a recent paper, Kee et al. [Appl. Opt. 59, 9434 (2020)APOPAI0003-693510.1364/AO.405663] use a multilayer perceptron neural network to classify objects in imagery after degradation through atmospheric turbulence. They also estimate turbulence stren
Autor:
Nicolas Verdier, Clémence Agrapart, Jean Michel Papy, Jean Baptiste Renard, Maximilien Lefevre
Publikováno v:
Applied optics
Applied optics, Optical Society of America, 2020, 59 (34), pp.10892. ⟨10.1364/AO.408959⟩
Applied optics, Optical Society of America, 2020, 59 (34), pp.10892. ⟨10.1364/AO.408959⟩
International audience; The light optical aerosols counter (LOAC) instrument is an optical aerosol counter that allows atmospheric particles from 0.2 to 50 µm to be individually counted and classified by size. The scattered light due to the interact
Autor:
René Berlich, Sjoerd Stallinga
Publikováno v:
Applied Optics, 59(22)
A practical method for determining wavefront aberrations in optical systems based on the acquisition of an extended, unknown object is presented. The approach utilizes a conventional phase diversity approach in combination with a pupil-engineered, he
Publikováno v:
Applied Optics Vol. 59, Issue 13, pp. D81-D88 (2020)
Recent methods for phase unwrapping in the presence of noise include denoising algorithms to filter out noise as a preprocessing stage. However, including a denoising stage increases the overall computational complexity resulting in long execution ti
Autor:
Giorgio S. Senesi, Jader Cabral, Matheus C. S. Ribeiro, Gustavo Nicolodelli, Cícero Cena, Bruno S. Marangoni, Charles Kiefer
Publikováno v:
Applied optics (2004) 59 (2020): 10043–10048. doi:10.1364/AO.409029
info:cnr-pdr/source/autori:Ribeiro, Matheus C. S.; Senesi, Giorgio S.; Cabral, Jader S.; Cena, Cicero; Marangoni, Bruno S.; Kiefer, Charles; Nicolodelli, Gustavo/titolo:Evaluation of rice varieties using LIBS and FTIR techniques associated with PCA and machine learning algorithms/doi:10.1364%2FAO.409029/rivista:Applied optics (2004)/anno:2020/pagina_da:10043/pagina_a:10048/intervallo_pagine:10043–10048/volume:59
info:cnr-pdr/source/autori:Ribeiro, Matheus C. S.; Senesi, Giorgio S.; Cabral, Jader S.; Cena, Cicero; Marangoni, Bruno S.; Kiefer, Charles; Nicolodelli, Gustavo/titolo:Evaluation of rice varieties using LIBS and FTIR techniques associated with PCA and machine learning algorithms/doi:10.1364%2FAO.409029/rivista:Applied optics (2004)/anno:2020/pagina_da:10043/pagina_a:10048/intervallo_pagine:10043–10048/volume:59
Laser-induced breakdown spectroscopy (LIBS) for atomic multi-elementary analyses, and Fourier transform infrared spectroscopy (FTIR) for molecular identification, are often suggested as the most versatile spectroscopic techniques. The present work ai
Autor:
Timothy J. Holmes, Yi-Hwa Liu
Publikováno v:
Applied Optics. 28:4930
A maximum likelihood based iterative algorithm adapted from nuclear medicine imaging for noncoherent optical imaging was presented in a previous publication with some initial computer-simulation testing. This algorithm is identical in form to that pr