Robust Scene Classification

Robust Scene Classification is a scene classification framework that belongs to the class of computer vision methodologies and is distinguished by its capacity to maintain high accuracy and reliability under varying environmental conditions, occlusions, scale changes, and domain shifts.

56

Publications

2.7K

Citations

223

Authors

99

Institutions

Publications per year

2017–2026

25

Authors

223

  1. HP
    Huy Phan

    University of Lübeck, Germany

    2 publications · 39 citations

    2

    h-index

  2. LF
    Li Fei-Fei

    Stanford University, United States

    2 publications · 526 citations

    2

    h-index

  3. YX
    Yi Xu

    Shanghai Jiao Tong University, China

    2 publications · 76 citations

    2

    h-index

  4. RP
    Ramaswamy Palaniappan

    University of Essex, United Kingdom

    2 publications · 39 citations

    2

    h-index

  5. DG
    Daniel G. Aliaga

    Purdue University West Lafayette, United States

    2 publications · 76 citations

    2

    h-index

1–5 of 223

Venues

  1. Pattern Recognition

    3 publications · 215 citations

    3

    h-index

  2. 3

    h-index

  3. IEEE Geoscience and Remote Sensing Letters

    GRSL · 3 publications · 57 citations

    2

    h-index

  4. 2009 IEEE Conference on Computer Vision and Pattern Recognition

    Conference · 2 publications · 526 citations

    2

    h-index

  5. 2

    h-index

1–5