Výsledky vyhledávání - "Wilkinson, M. H. F."

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Generalized Relevance Learning Grassmann Quantization

Autor: Mohammadi, M., Babai, M., Wilkinson, M. H. F.

Due to advancements in digital cameras, it is easy to gather multiple images (or videos) from an object under different conditions. Therefore, image-set classification has attracted more attention, and different solutions were proposed to model them.

Externí odkaz: http://arxiv.org/abs/2403.09183

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Signal-background separation and energy reconstruction of gamma rays using pattern spectra and convolutional neural networks for the Small-Sized Telescopes of the Cherenkov Telescope Array

Autor: Aschersleben, J., Arnesen, T. T. H., Peletier, R. F., Vecchi, M., Vlasakidis, C., Wilkinson, M. H. F.

Imaging Atmospheric Cherenkov Telescopes (IACTs) detect very high-energy gamma rays from ground level by capturing the Cherenkov light of the induced particle showers. Convolutional neural networks (CNNs) can be trained on IACT camera images of such

Externí odkaz: http://arxiv.org/abs/2307.05301

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Event reconstruction using pattern spectra and convolutional neural networks for the Cherenkov Telescope Array

Autor: Aschersleben, J., Vecchi, M., Wilkinson, M. H. F., Peletier, R. F.

The Cherenkov Telescope Array (CTA) is the future observatory for ground-based imaging atmospheric Cherenkov telescopes. Each telescope will provide a snapshot of gamma-ray induced particle showers by capturing the induced Cherenkov emission at groun

Externí odkaz: http://arxiv.org/abs/2302.11876

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A comparative study of source-finding techniques in HI emission line cubes using SoFiA, MTObjects, and supervised deep learning

Autor: Barkai, J. A., Verheijen, M. A. W., Martínez, E. T., Wilkinson, M. H. F.

Publikováno v: A&A 670, A55 (2023)

The 21 cm spectral line emission of atomic neutral hydrogen (HI) is one of the primary wavelengths observed in radio astronomy. However, the signal is intrinsically faint and the HI content of galaxies depends on the cosmic environment, requiring lar

Externí odkaz: http://arxiv.org/abs/2211.12809

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Application of pattern spectra and convolutional neural networks to the analysis of simulated Cherenkov Telescope Array data

Autor: Aschersleben, J., Peletier, R. F., Vecchi, M., Wilkinson, M. H. F.

The Cherenkov Telescope Array (CTA) will be the next generation gamma-ray observatory and will be the major global instrument for very-high-energy astronomy over the next decade, offering 5 - 10 x better flux sensitivity than current generation gamma

Externí odkaz: http://arxiv.org/abs/2108.00834

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