Feature-based Representation

Feature-Based Representation is a cognitive model of semantic memory that represents concepts as structured collections of perceptual, functional, and categorical features, distinguishing itself from holistic or associative models by emphasizing decompositional attribute-level information as the basis for conceptual knowledge.

1.7K

Publications

137.3K

Citations

6K

Authors

1.4K

Institutions

Publications per year

2017–2026

1.1K

Variants

Feature-based Model Of Semantic Memory

Authors

6K

  1. QZ
    Quan Zou

    University of Electronic Science and Technology of China, China

    12 publications · 1.1K citations

    12

    h-index

  2. LW
    Leyi Wei

    Shandong University, China

    11 publications · 2.1K citations

    10

    h-index

  3. SY
    Shuicheng Yan

    National University of Singapore, Singapore

    7 publications · 1.6K citations

    7

    h-index

  4. HL
    Haizhou Li

    National University of Singapore, Singapore

    7 publications · 347 citations

    7

    h-index

  5. RS
    Ran Su

    Tianjin University, China

    7 publications · 1.3K citations

    7

    h-index

1–5 of 6K

Venues

  1. arXiv (Cornell University)

    Repository · 100 publications · 4.8K citations

    35

    h-index

  2. 26

    h-index

  3. IEEE Transactions on Image Processing

    33 publications · 2.4K citations

    25

    h-index

  4. 24

    h-index

  5. IEEE Access

    43 publications · 1.5K citations

    23

    h-index

1–5