Fusion Rule Learning

Fusion Rule Learning is a machine learning methodology that specifically involves the acquisition and optimization of decision rules for combining outputs from multiple classifiers or sensors at the decision level to enhance overall system performance.

23

Publications

785

Citations

56

Authors

32

Institutions

Publications per year

2017–2026

7

Authors

56

  1. KG
    Kripabandhu Ghosh

    Indian Institute of Technology Kharagpur, India

    1 publications · 22 citations

    1

    h-index

  2. CC
    Chia-Wei Chang

    National Chung Hsing University, Taiwan

    1 publications · 16 citations

    1

    h-index

  3. WL
    Wei Liu

    Shanghai Jiao Tong University, China

    1 publications · 10 citations

    1

    h-index

  4. XS
    Xuequn Shang

    Northwestern Polytechnical University, China

    1 publications · 10 citations

    1

    h-index

  5. DM
    Darío Maravall

    Universidad Politécnica de Madrid, Spain

    1 publications · 17 citations

    1

    h-index

1–5 of 56

Venues

  1. Soft Computing

    2 publications · 56 citations

    2

    h-index

  2. IEEE Journal of Oceanic Engineering

    1 publications · 23 citations

    1

    h-index

  3. Personal and Ubiquitous Computing

    1 publications · 37 citations

    1

    h-index

  4. Information Fusion

    1 publications · 13 citations

    1

    h-index

  5. Kybernetes

    1 publications · 28 citations

    1

    h-index

1–5