[HTML][HTML] Cosmic-ray extremely distributed observatory

P Homola, D Beznosko, G Bhatta, Ł Bibrzycki… - Symmetry, 2020 - mdpi.com
The Cosmic-Ray Extremely Distributed Observatory (CREDO) is a newly formed, global
collaboration dedicated to observing and studying cosmic rays (CR) and cosmic-ray …

[HTML][HTML] The role of citizen science mobile apps in facilitating a contemporary digital agora

GG Hognogi, M Meltzer, F Alexandrescu… - Humanities and Social …, 2023 - nature.com
The advancements in digital technologies, especially for mobile apps, enabled simplified
data collection methods. Consequently, through Citizen Science, numerous opportunities …

[HTML][HTML] The practice of detecting potential cosmic rays using CMOs cameras: hardware and algorithms

T Hachaj, M Piekarczyk - Sensors, 2023 - mdpi.com
In this paper, we discuss a practice of potential cosmic ray detection using off-the-shelves
CMOS cameras. We discuss and presents the limitations of up-to-date hardware and …

[HTML][HTML] CNN-based classifier as an offline trigger for the CREDO experiment

M Piekarczyk, O Bar, Ł Bibrzycki, M Niedźwiecki… - Sensors, 2021 - mdpi.com
Gamification is known to enhance users' participation in education and research projects
that follow the citizen science paradigm. The Cosmic Ray Extremely Distributed Observatory …

[HTML][HTML] Zernike moment based classification of cosmic ray candidate hits from CMOS sensors

O Bar, Ł Bibrzycki, M Niedźwiecki, M Piekarczyk… - Sensors, 2021 - mdpi.com
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 …

Differentiating signal from artefacts in cosmic ray detection: Applying Siamese spiking neural networks to CREDO experimental data

M Pabian, D Rzepka, Ł Bibrzycki, M Pawlak - Measurement, 2023 - Elsevier
Abstract The Cosmic Ray Extremely Distributed Observatory (CREDO) is an international
research consortium aimed at observing high energy cosmic ray particles. The associated …

[HTML][HTML] Recognition of cosmic ray images obtained from CMOS sensors used in mobile phones by approximation of uncertain class assignment with deep …

T Hachaj, Ł Bibrzycki, M Piekarczyk - Sensors, 2021 - mdpi.com
In this paper, we describe the convolutional neural network (CNN)-based approach to the
problems of categorization and artefact reduction of cosmic ray images obtained from CMOS …

Fast training data generation for machine learning analysis of cosmic ray showers

T Hachaj, Ł Bibrzycki, M Piekarczyk - IEEE Access, 2023 - ieeexplore.ieee.org
Applying Machine Learning (ML) methods for the analysis of muon lateral distributions in
Extensive Air Showers detected by citizen science projects, while taking into account the …

Searching of Potentially Anomalous Signals in Cosmic-Ray Particle Tracks Images Using Rough k-Means Clustering Combined with Eigendecomposition-Derived …

T Hachaj, M Piekarczyk, J Wąs - International Joint Conference on Rough …, 2023 - Springer
Our work presents the application of the rough sets method in the field of astrophysics for the
analysis of observational data recorded by the Cosmic Ray Extremely Distributed …

[HTML][HTML] On the Search for Potentially Anomalous Traces of Cosmic Ray Particles in Images Acquired by Cmos Detectors for a Continuous Stream of Emerging …

M Piekarczyk, T Hachaj - Sensors, 2024 - mdpi.com
In this paper we propose the method for detecting potential anomalous cosmic ray particle
tracks in big data image dataset acquired by Complementary Metal-Oxide-Semiconductors …