Real-time Feature Detection

Real-Time Feature Detection is a computational method in computer vision that enables the immediate identification and localization of distinctive image features with minimal latency, ensuring processing rates sufficient to support continuous, time-sensitive applications.

480

Publications

47.4K

Citations

1.8K

Authors

666

Institutions

Publications per year

2017–2026

197

Authors

1.8K

  1. JO
    Jun Ohya

    Advanced Telecommunications Research Institute International, Japan

    4 publications · 199 citations

    4

    h-index

  2. CM
    Chris Messom

    Massey University, New Zealand

    3 publications · 67 citations

    3

    h-index

  3. AL
    Andre L. C. Barczak

    Massey University, New Zealand

    3 publications · 74 citations

    3

    h-index

  4. BL
    Bo Li

    Beihang University, China

    2 publications · 82 citations

    2

    h-index

  5. GZ
    Guyue Zhang

    Fudan University, China

    2 publications · 31 citations

    2

    h-index

1–5 of 1.8K

Venues

  1. Sensors

    13 publications · 600 citations

    13

    h-index

  2. IEEE Access

    11 publications · 558 citations

    11

    h-index

  3. Computers and Electronics in Agriculture

    8 publications · 954 citations

    8

    h-index

  4. Journal of Real-Time Image Processing

    5 publications · 172 citations

    5

    h-index

  5. IEEE Sensors Journal

    5 publications · 302 citations

    5

    h-index

1–5