First Full-Event Reconstruction from Imaging Atmospheric Cherenkov Telescope Real Data with Deep Learning
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Abstract (arXiv)
The Cherenkov Telescope Array is the future of ground-based gamma-ray astronomy. Its first prototype telescope built on-site, the Large Size Telescope 1, is currently under commissioning and taking its first scientific data. In this paper, we present for the first time the development of a full-event reconstruction based on deep convolutional neural networks and its application to real data. We show that it outperforms the standard analysis, both on simulated and on real data, thus validating the deep approach for the CTA data analysis. This work also illustrates the difficulty of moving from simulated data to actual data.
Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Builds on 3 of its 21 references that are in the map. First posted on arXiv 31 May 2021.
Builds on
3 of 21 references.
References · 3
- 2015Deep Residual Learning for Image Recognitioncited by 51,809
- 2017Squeeze-and-Excitation Networkscited by 4,763
- 2020SAUNet: Shape Attentive U-Net for Interpretable Medical Image Segmentationcited by 19
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.