Distributed Detection Fusion

Distributed Detection Fusion is a decision-level fusion framework in which multiple spatially separated sensors independently perform local detection and transmit compressed binary decisions to a central fusion center that combines them to produce a global hypothesis about a common phenomenon.

33

Publications

1.7K

Citations

71

Authors

44

Institutions

Publications per year

2017–2026

3

Authors

71

  1. PW
    Peter Willett

    University of Connecticut, United States

    4 publications · 603 citations

    4

    h-index

  2. HA
    H. Ahmadi

    IBM Research - Thomas J. Watson Research Center, United States

    2 publications · 70 citations

    2

    h-index

  3. AV
    Azadeh Vosoughi

    University of Central Florida, United States

    2 publications · 70 citations

    2

    h-index

  4. JP
    Jintae Park

    Gwangju Institute of Science and Technology, South Korea

    2 publications · 44 citations

    2

    h-index

  5. VK
    Vivek K Goyal

    Massachusetts Institute of Technology, United States

    2 publications · 51 citations

    2

    h-index

1–5 of 71

Venues

  1. IEEE Transactions on Signal Processing

    6 publications · 308 citations

    6

    h-index

  2. 4

    h-index

  3. IEEE Transactions on Information Theory

    4 publications · 205 citations

    4

    h-index

  4. 2

    h-index

  5. IEEE Transactions on Wireless Communications

    1 publications · 30 citations

    1

    h-index

1–5