Distance Metrics

Distance Metrics is a formal mathematical framework that quantifies the dissimilarity between data points in a geometric space by defining a specific function satisfying metric properties such as non-negativity, identity of indiscernibles, symmetry, and the triangle inequality.

1.6K

Publications

115.7K

Citations

3.7K

Authors

1.4K

Institutions

Publications per year

2017–2026

411

Authors

3.7K

  1. EK
    Erdal Karapınar

    Atilim University, Türkiye

    9 publications · 200 citations

    9

    h-index

  2. JL
    Jiwen Lu

    Tsinghua University, China

    9 publications · 973 citations

    9

    h-index

  3. BL
    Binbin Lu

    Wuhan University, China

    7 publications · 762 citations

    7

    h-index

  4. PH
    Paul Harris

    Rothamsted Research, United Kingdom

    7 publications · 762 citations

    7

    h-index

  5. FM
    Facundo Mémoli

    The Ohio State University, United States

    6 publications · 343 citations

    6

    h-index

1–5 of 3.7K

Venues

  1. arXiv (Cornell University)

    Repository · 43 publications · 1.2K citations

    22

    h-index

  2. Fuzzy Sets and Systems

    19 publications · 2.9K citations

    15

    h-index

  3. Pattern Recognition

    15 publications · 1.1K citations

    14

    h-index

  4. IEEE Transactions on Image Processing

    13 publications · 1.8K citations

    13

    h-index

  5. Proceedings of the American Mathematical Society

    PROC · 18 publications · 705 citations

    13

    h-index

1–5