Real-time Performance Profiling

Real-Time Performance Profiling is a computational methodology that continuously monitors and analyzes the execution behavior of augmented reality systems during operation to identify performance bottlenecks with minimal latency, distinguishing it from offline profiling techniques by its emphasis on immediate feedback and dynamic adaptability.

16

Publications

671

Citations

71

Authors

30

Institutions

Publications per year

2017–2026

8

Authors

71

  1. FR
    Florian Reinke

    University Hospital Münster, Germany

    1 publications · 15 citations

    1

    h-index

  2. XL
    Xuanzhe Liu

    Peking University, China

    1 publications · 75 citations

    1

    h-index

  3. RV
    R. Villari

    National Agency for New Technologies, Energy and Sustainable Economic Development, Italy

    1 publications · 12 citations

    1

    h-index

  4. XX
    Xianghua Xu

    Hangzhou Dianzi University, China

    1 publications · 10 citations

    1

    h-index

  5. NP
    Nikos Petrellis

    Technological Educational Institute of Thessaly, Greece

    1 publications · 28 citations

    1

    h-index

1–5 of 71

Venues

  1. arXiv (Cornell University)

    Repository · 1 publications · 16 citations

    1

    h-index

  2. IEEE Internet of Things Journal

    1 publications · 168 citations

    1

    h-index

  3. IEEE Transactions on Mobile Computing

    TMCCI · 1 publications · 75 citations

    1

    h-index

  4. Fusion Engineering and Design

    1 publications · 12 citations

    1

    h-index

  5. 1

    h-index

1–5