Sparse Feature Aggregation

Sparse Feature Aggregation is a computational method that selectively combines a small subset of salient features from high-dimensional, sparsely activated representations to produce compact and informative aggregate feature vectors.

26

Publications

1.7K

Citations

99

Authors

42

Institutions

Publications per year

2017–2026

21

Authors

99

  1. JP
    Jinshan Pan

    KTH Royal Institute of Technology, Sweden

    3 publications · 524 citations

    3

    h-index

  2. CH
    Congrui Hetang

    Beihang University, China

    2 publications · 42 citations

    2

    h-index

  3. ML
    Mingqiang Li

    Chinese University of Hong Kong, Hong Kong SAR China

    2 publications · 451 citations

    2

    h-index

  4. XC
    Xiang Chen

    Shenyang Aerospace University, China

    2 publications · 451 citations

    2

    h-index

  5. KL
    Kyogu Lee

    Seoul National University, South Korea

    1 publications · 17 citations

    1

    h-index

1–5 of 99

Venues

  1. arXiv (Cornell University)

    Repository · 4 publications · 96 citations

    4

    h-index

  2. IEEE Access

    1 publications · 16 citations

    1

    h-index

  3. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 1 publications · 191 citations

    1

    h-index

  4. 1

    h-index

  5. IEEE Transactions on Multimedia

    1 publications · 16 citations

    1

    h-index

1–5