Sensor Data Fusion

Sensor Data Fusion is a process within distributed sensing systems that integrates complementary and redundant information from multiple heterogeneous sensors in sensor networks for mining to produce more accurate, consistent, and reliable situational representations than could be achieved by individual sensor inputs alone.

2K

Publications

98.2K

Citations

5.9K

Authors

1.7K

Institutions

Publications per year

2017–2026

759

Authors

5.9K

  1. PK
    Pramod K. Varshney

    Syracuse University, United States

    22 publications · 3.2K citations

    18

    h-index

  2. EB
    Erik Blasch

    United States Air Force Research Laboratory, United States

    14 publications · 613 citations

    12

    h-index

  3. SS
    Shuli Sun

    Heilongjiang University, China

    12 publications · 676 citations

    12

    h-index

  4. UM
    Uwe Mönks

    Ostwestfalen-Lippe University of Applied Sciences and Arts, Germany

    9 publications · 155 citations

    9

    h-index

  5. PW
    Peter Willett

    University of Connecticut, United States

    9 publications · 725 citations

    9

    h-index

1–5 of 5.9K

Venues

  1. Information Fusion

    63 publications · 8.2K citations

    40

    h-index

  2. Sensors

    107 publications · 4.6K citations

    36

    h-index

  3. IEEE Access

    42 publications · 1.7K citations

    27

    h-index

  4. IEEE Sensors Journal

    40 publications · 2K citations

    26

    h-index

  5. 25

    h-index

1–5