Consensus Fusion

Consensus Fusion is a decision-level fusion methodology in multi-sensor tracking systems that belongs to the class of track-to-track fusion techniques and is distinguished by its iterative exchange of local estimates among sensors to achieve global agreement on fused tracks through mutual adjustment of tracking information.

50

Publications

2.8K

Citations

147

Authors

81

Institutions

Publications per year

2017–2026

21

Authors

147

  1. TL
    Tiancheng Li

    Northwestern Polytechnical University, China

    4 publications · 219 citations

    4

    h-index

  2. FS
    Florentín Smarandache

    University of New Mexico, United States

    3 publications · 196 citations

    3

    h-index

  3. LA
    Leman Akoglu

    Carnegie Mellon University, United States

    2 publications · 61 citations

    2

    h-index

  4. QP
    Quan Pan

    Northwestern Polytechnical University, China

    2 publications · 154 citations

    2

    h-index

  5. BD
    B.V. Dasarathy

    Indian Institute of Science Bangalore, India

    2 publications · 79 citations

    2

    h-index

1–5 of 147

Venues

  1. 3

    h-index

  2. arXiv (Cornell University)

    Repository · 2 publications · 35 citations

    2

    h-index

  3. IEEE Transactions on Image Processing

    2 publications · 44 citations

    2

    h-index

  4. Information Fusion

    2 publications · 55 citations

    2

    h-index

  5. 2

    h-index

1–5