Deep Edge Detection

Deep Edge Detection is an academic concept referring to a class of computational methods in computer vision that leverage deep neural networks to automatically identify and localize semantic boundaries within images, distinguished from traditional edge detection by its reliance on hierarchical feature learning and end-to-end optimization.

198

Publications

18.3K

Citations

789

Authors

319

Institutions

Publications per year

2017–2026

178

Authors

789

  1. ÁD
    Ángel D. Sappa

    Computer Vision Center

    4 publications · 260 citations

    4

    h-index

  2. ZT
    Zhuowen Tu

    University of California, Los Angeles, United States

    3 publications · 4.2K citations

    3

    h-index

  3. XS
    Xavier Soria Poma

    Escuela Superior Politecnica del Litoral, Ecuador

    3 publications · 241 citations

    3

    h-index

  4. SX
    Saining Xie

    Meta (Israel), Israel

    3 publications · 4.2K citations

    3

    h-index

  5. LZ
    Le Zhang

    Agency for Science, Technology and Research, Singapore

    3 publications · 175 citations

    3

    h-index

1–5 of 789

Venues

  1. arXiv (Cornell University)

    Repository · 12 publications · 624 citations

    12

    h-index

  2. Remote Sensing

    10 publications · 282 citations

    10

    h-index

  3. IEEE Access

    8 publications · 470 citations

    8

    h-index

  4. Neurocomputing

    5 publications · 157 citations

    5

    h-index

  5. IEEE Transactions on Image Processing

    5 publications · 389 citations

    5

    h-index

1–5