SOURCE-LINKED INTELLIGENCE
ResoSeg: Resonance Tagger using Transformer and Segment Model
Deep learning has been widely applied across many areas of experimental high-energy physics, yet existing models address only event-level classification or object tagging and therefore still require reconstruction algorithms tailored to each decay channel. We present the first application of segmentation to resonance tagging at BESIII and introduce ResoSeg, a deep learning model that jointly performs particle-level segmentation and event-level classification, enabling a one-pass analysis of resonance to anything decays while precisely reconstructing the relevant resonance properties. We demons
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- arXiv · AI, language, vision and robotics · 2026-09-11T09:08:28.000Z
First collected: 2026-09-20T18:22:04.777Z. This is not the publication date.