Computational Methods in Spectral Imaging
Pölönen, I. (2023). Computational Methods in Spectral Imaging. In P. Neittaanmäki, & M.-L. Rantalainen (Eds.), Impact of Scientific Computing on Science and Society (pp. 295-313). Springer. Computational Methods in Applied Sciences, 58. https://doi.org/10.1007/978-3-031-29082-4_17
Julkaistu sarjassa
Computational Methods in Applied SciencesTekijät
Päivämäärä
2023Oppiaine
TietotekniikkaLaskennallinen tiedeComputing, Information Technology and MathematicsMathematical Information TechnologyComputational ScienceComputing, Information Technology and MathematicsPääsyrajoitukset
Embargo päättyy: 2025-07-08Pyydä artikkeli tutkijalta
Tekijänoikeudet
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
Spectral imaging is an evolving technology with numerous applications. These images can be computationally processed in several ways. In addition to machine learning methods, spectral images can be processed mathematically by modelling or by combining both approaches. This chapter looks at spectral imaging and the computational methods commonly used in it. We review methods related to preprocessing, modelling, and machine learning, and become familiar with some applications.
Julkaisija
SpringerEmojulkaisun ISBN
978-3-031-29081-7Kuuluu julkaisuun
Impact of Scientific Computing on Science and SocietyISSN Hae Julkaisufoorumista
1871-3033Asiasanat
Julkaisu tutkimustietojärjestelmässä
https://converis.jyu.fi/converis/portal/detail/Publication/183943191
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