Zernike Moment Based Classification of Cosmic Ray Candidate Hits from CMOS Sensors

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...

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主要な著者:	Olaf Bar, Łukasz Bibrzycki, Michał Niedźwiecki, Marcin Piekarczyk, Krzysztof Rzecki, Tomasz Sośnicki, Sławomir Stuglik, Michał Frontczak, Piotr Homola, David E. Alvarez-Castillo, Thomas Andersen, Arman Tursunov
フォーマット:	Artigo
言語:	Inglês
出版事項:	MDPI AG 2021-11-01
シリーズ:	Sensors
主題:	CMOS sensors feature-based classification Zernike moments machine learning computer vision
オンライン･アクセス:	https://www.mdpi.com/1424-8220/21/22/7718
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