Dense Feature Representation

Dense Feature Representation is a type of feature representation in which each feature vector is characterized by a high-dimensional, continuous, and typically non-sparse numerical encoding that captures rich, distributed patterns across the entire input space.

270

Publications

28.1K

Citations

1K

Authors

371

Institutions

Publications per year

2017–2026

184

Authors

1K

  1. LF
    Li Fei-Fei

    Stanford University, United States

    3 publications · 1.4K citations

    3

    h-index

  2. AT
    Akihiko Torii

    Tokyo Institute of Technology, Japan

    3 publications · 1.3K citations

    3

    h-index

  3. CS
    Changyin Sun

    Southeast University, China

    3 publications · 289 citations

    3

    h-index

  4. WZ
    Wangmeng Zuo

    Harbin Institute of Technology, China

    3 publications · 123 citations

    3

    h-index

  5. CS
    Chunhua Shen

    The University of Adelaide, Australia

    3 publications · 251 citations

    3

    h-index

1–5 of 1K

Venues

  1. arXiv (Cornell University)

    Repository · 27 publications · 1.5K citations

    18

    h-index

  2. 9

    h-index

  3. 7

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  4. IEEE Access

    7 publications · 404 citations

    7

    h-index

  5. 6

    h-index

1–5