Zernike moment based classification of cosmic ray candidate hits from cmos sensors

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F47813059%3A19630%2F21%3AA0000153" target="_blank" >RIV/47813059:19630/21:A0000153 - isvavai.cz</a>
Result on the web
<a href="https://www.mdpi.com/1424-8220/21/22/7718" target="_blank" >https://www.mdpi.com/1424-8220/21/22/7718</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.3390/s21227718" target="_blank" >10.3390/s21227718</a>

Result language
angličtina
Original language name
Zernike moment based classification of cosmic ray candidate hits from cmos sensors
Original language description
Reliable tools for artefact rejection and signal classification are a must for cosmic ray detection experiments based on CMOS technology. In this paper, we analyse the fitness of several feature-based statistical classifiers for the classification of particle candidate hits in four categories: spots, tracks, worms and artefacts. We use Zernike moments of the image function as feature carriers and propose a preprocessing and denoising scheme to make the feature extraction more efficient. As opposed to convolution neural network classifiers, the feature-based classifiers allow for establishing a connection between features and geometrical properties of candidate hits. Apart from basic classifiers we also consider their ensemble extensions and find these extensions generally better performing than basic versions, with an average recognition accuracy of 88%.
Czech name
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Czech description
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Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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OECD FORD branch
10308 - Astronomy (including astrophysics,space science)

Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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