Intelligent Document Processing

Intelligent Document Processing is an academic concept referring to a computational method that automates the extraction, interpretation, and classification of information from unstructured or semi-structured documents by integrating optical character recognition, natural language processing, and machine learning to enable context-aware document analysis in public sector automation.

407

Publications

17.9K

Citations

1.1K

Authors

391

Institutions

Publications per year

2017–2026

104

Authors

1.1K

  1. CY
    Ching Y. Suen

    Concordia University, Canada

    10 publications · 395 citations

    10

    h-index

  2. BC
    B.B. Chaudhuri

    Indian Statistical Institute, India

    7 publications · 309 citations

    7

    h-index

  3. KR
    Kaushik Roy

    West Bengal State University, India

    6 publications · 226 citations

    6

    h-index

  4. AB
    Abdel Belaı̈d

    Laboratoire Lorrain de Recherche en Informatique et ses Applications, France

    5 publications · 117 citations

    5

    h-index

  5. UP
    Umapada Pal

    Indian Statistical Institute, India

    5 publications · 284 citations

    5

    h-index

1–5 of 1.1K

Venues

  1. arXiv (Cornell University)

    Repository · 12 publications · 269 citations

    12

    h-index

  2. 11

    h-index

  3. 10

    h-index

  4. Pattern Recognition

    7 publications · 358 citations

    7

    h-index

  5. 6

    h-index

1–5