20-24 October 2025
Mexico/General timezone
- xixmwpf_2025@googlegroups.com
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Contribution Poster Presentation
Speakers
Primary authors
- Mr. Felipe OROZCO (Universidad de Guadalajara / CADS)
Co-authors
- Dr. Eduardo DE LA FUENTE ACOSTA (Universidad de Guadalajara)
- Prof. Saul CUEN-ROCHIN (Tecnologico de Monterrey)
Summary
We present research on classifying high-energy events for simulated Water Cherenkov detectors. The goal is to evaluate the performance of supervised learning models based on the Vision Transformer (ViT) architecture for distinguishing between two types of high-energy events: electron-neutrino and gamma events. The Vision Transformer achieved up to 85% accuracy and a maximum ROC-AUC of 0.95, significantly outperforming traditional convolutional and resnet neural network architectures.
correo electrónico
felipe.orozco@udg.mx
Speaker
Felipe de Jesus Orozco Luna
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