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

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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Bibliographic Details
Main Authors: 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
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Sensors
Subjects:
CMOS sensors
feature-based classification
Zernike moments
machine learning
computer vision
Online Access:https://www.mdpi.com/1424-8220/21/22/7718

Internet

https://www.mdpi.com/1424-8220/21/22/7718

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