all AI news
High-energy physics image classification: A Survey of Jet Applications
March 19, 2024, 4:50 a.m. | Hamza Kheddar, Yassine Himeur, Abbes Amira, Rachik Soualah
cs.CV updates on arXiv.org arxiv.org
Abstract: In recent times, the fields of high-energy physics (HEP) experimentation and phenomenological studies have seen the integration of machine learning (ML) and its specialized branch, deep learning (DL). This survey offers a comprehensive assessment of these applications within the realm of various DL approaches. The initial segment of the paper introduces the fundamentals encompassing diverse particle physics types and establishes criteria for evaluating particle physics in tandem with learning models. Following this, a comprehensive taxonomy …
abstract applications arxiv assessment classification cs.cv deep learning eess.iv energy experimentation fields hep-ex hep-ph image integration machine machine learning physics studies survey type
More from arxiv.org / cs.CV updates on arXiv.org
Jobs in AI, ML, Big Data
AI Research Scientist
@ Vara | Berlin, Germany and Remote
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Data Analyst (Digital Business Analyst)
@ Activate Interactive Pte Ltd | Singapore, Central Singapore, Singapore