Human-in-the-loop Data Collection

Human-In-The-Loop Data Collection is a data acquisition methodology in which human agents are actively and iteratively integrated into the data generation, annotation, or refinement process to enhance data quality, contextual accuracy, or system performance beyond what automated methods alone can achieve.

16

Publications

869

Citations

67

Authors

25

Institutions

Publications per year

2017–2026

14

Variants

Hitl Data Collection

Authors

67

  1. EK
    Eser Kandogan

    IBM Research - Almaden, United States

    2 publications · 34 citations

    2

    h-index

  2. FJ
    Fabrice Jotterand

    Medical College of Wisconsin, United States

    1 publications · 52 citations

    1

    h-index

  3. GH
    Geert Heyman

    KU Leuven, Belgium

    1 publications · 17 citations

    1

    h-index

  4. DN
    David Nunes

    University of Coimbra, Portugal

    1 publications · 274 citations

    1

    h-index

  5. YY
    Yiwei Yang

    University of Washington, United States

    1 publications · 19 citations

    1

    h-index

1–5 of 67

Venues

  1. Behavior Research Methods

    BRM · 1 publications · 17 citations

    1

    h-index

  2. Science and Engineering Ethics

    1 publications · 52 citations

    1

    h-index

  3. IUI Workshops

    1 publications · 19 citations

    1

    h-index

  4. IEEE Communications Surveys & Tutorials

    ComST · 1 publications · 274 citations

    1

    h-index

  5. IFAC-PapersOnLine

    1 publications · 44 citations

    1

    h-index

1–5