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Steven Guan, Ko-Tsung Hsu and Parag V. Chitnis
Simulation tools for photoacoustic wave propagation have played a key role in advancing photoacoustic imaging by providing quantitative and qualitative insights into parameters affecting image quality. Classical methods for numerically solving the photoa...
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Thomas J. Tewes, Michael C. Welle, Bernd T. Hetjens, Kevin Saruni Tipatet, Svyatoslav Pavlov, Frank Platte and Dirk P. Bockmühl
Numerous publications showing that robust prediction models for microorganisms based on Raman micro-spectroscopy in combination with chemometric methods are feasible, often with very precise predictions. Advances in machine learning and easier accessibil...
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Osman Isa Çelik, Gürcan Büyüksalih and Cem Gazioglu
The spatial and spectral information brought by the Very High Resolution (VHR) and multispectral satellite images present an advantage for Satellite-Derived Bathymetry (SDB), especially in shallow-water environments with dense wave patterns. This work fo...
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Oleg A. Logachev,Sergei N. Fedorov,Valeriy V. Yashchenko
Pág. 27 - 31
Boolean functions that are maximally nonlinear, that is, having maximal Hamming distance from the set of affine Boolean functions, are widely used, for example, in the construction of ciphers, since they increase their security against ...
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Sean McCarthy, Summer Crawford, Christopher Wood, Mark D. Lewis, Jason K. Jolliff, Paul Martinolich, Sherwin Ladner, Adam Lawson and Marcos Montes
Here we present a machine-learning-based method for utilizing traditional ocean-viewing satellites to perform automated atmospheric correction of nanosatellite data. These sensor convolution techniques are required because nanosatellites do not usually p...
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