Optical Character Recognition

Optical Character Recognition is a computational technique that enables the identification and conversion of printed or handwritten characters within digital images into machine-encoded text, thereby facilitating the digitization and analysis of historical and scholarly documents in the field of Digital Humanities.

9.3K

Publications

468.2K

Citations

18.5K

Authors

3.4K

Institutions

Publications per year

2017–2026

2.6K

Authors

18.5K

  1. UP
    Umapada Pal

    Indian Statistical Institute, India

    95 publications · 5.2K citations

    38

    h-index

  2. DZ
    David Zhang

    Hong Kong Polytechnic University, Hong Kong SAR China

    54 publications · 7.6K citations

    36

    h-index

  3. BG
    Basilis Gatos

    National Centre of Scientific Research "Demokritos", Greece

    66 publications · 4.4K citations

    35

    h-index

  4. CY
    Ching Y. Suen

    Concordia University, Canada

    87 publications · 6.4K citations

    34

    h-index

  5. CL
    Cheng‐Lin Liu

    Chinese Academy of Sciences, China

    58 publications · 5K citations

    31

    h-index

1–5 of 18.5K

Venues

  1. Pattern Recognition

    589 publications · 48.9K citations

    118

    h-index

  2. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 137 publications · 27.9K citations

    79

    h-index

  3. Pattern Recognition Letters

    265 publications · 14.4K citations

    64

    h-index

  4. 57

    h-index

  5. arXiv (Cornell University)

    Repository · 130 publications · 7.3K citations

    41

    h-index

1–5