IJCAI

Vision Transformers for End-to-End Quark-Gluon Jet Classification from Calorimeter Images

用于量能器图像中夸克-胶子喷注端到端分类的视觉Transformer

Md Abrar Jahin, Shahriar Soudeep, Arian Rahman Aditta, M. F. Mridha, Nafiz Fahad, Md. Jakir Hossen

机构 * University of Southern California American International University-Bangladesh Khulna University of Engineering \& Technology Multimedia University 纠错

AI总结 本研究以2012年CMS开放数据为基础，系统评估ViT及ViT-CNN混合模型，发现其在夸克-胶子喷注分类任务中优于CNN基线，建立了相关系统框架与基准。

Comments Accepted in Third International Workshop on Generalizing from Limited Resources in the Open World Workshop at International Joint Conference on Artificial Intelligence (IJCAI) 2025