Concepedia

Explainable Image Classification

Explainable Image Classification is an image classification paradigm that, as a distinct contribution within computer vision research, integrates interpretability mechanisms to explicitly reveal the decision-making rationale of its predictions, thereby distinguishing itself from conventional image classification approaches by providing human-understandable justifications for model outputs.

220

Publications

20.5K

Citations

806

Authors

348

Institutions

Publications per year

2017–2026

213

Parents

Publications

220

On Pixel-Wise Explanations for Non-Linear Classifier Decisions by Layer-Wise Relevance Propagation

Sebastian Bach, Alexander Binder, Grégoire Montavon et al. · PLoS ONE · 2015 · 4.6K citations · Full text

, , +14

Grad-CAM++: Generalized Gradient-Based Visual Explanations for Deep Convolutional Networks

Aditya Chattopadhay, Anirban Sarkar, Prantik Howlader et al. · 2018 · 3.1K citations · Full text

, , +15

SmoothGrad: removing noise by adding noise

Daniel Smilkov, Nikhil Thorat, Been Kim et al. · arXiv (Cornell University) · 2017 · 755 citations · Full text

, , +16

Interpretation of Neural Networks Is Fragile

Amirata Ghorbani, Abubakar Abid, James Zou · Proceedings of the AAAI Conference on Artificial Intelligence · 2019 · 682 citations · Full text

, , +15

This Looks Like That: Deep Learning for Interpretable Image Recognition

Chaofan Chen, Oscar Li, Chaofan Tao et al. · arXiv (Cornell University) · 2018 · 567 citations · Full text

, , +14

1–5 of 220

Authors

806

  1. CC
    Chaofan Chen

    Duke University, United States

    5 publications · 1K citations

    5

    h-index

  2. CR
    Cynthia Rudin

    Duke University, United States

    5 publications · 1.2K citations

    5

    h-index

  3. BW
    Bowen Wang

    The University of Osaka, Japan

    4 publications · 173 citations

    4

    h-index

  4. HN
    Hajime Nagahara

    The University of Osaka, Japan

    4 publications · 173 citations

    4

    h-index

  5. LL
    Liangzhi Li

    The University of Osaka, Japan

    4 publications · 173 citations

    4

    h-index

1–5 of 806

Institutions

348

  1. Duke University

    Durham, United States

    6 h-index

    19 publications

    5K citations

  2. Technische Universität Berlin

    Berlin, Germany

    5 h-index

    15 publications

    23.6K citations

  3. Georgia Institute of Technology

    Atlanta, United States

    5 h-index

    20 publications

    749 citations

  4. The University of Osaka

    Osaka, Japan

    4 h-index

    22 publications

    926 citations

  5. Google (United States)

    Mountain View, United States

    4 h-index

    28 publications

    2.3K citations

  6. Massachusetts Institute of Technology

    Cambridge, United States

    4 h-index

    4 publications

    851 citations

  7. Emory University

    Atlanta, United States

    3 h-index

    4 publications

    120 citations

  8. Chinese Academy of Sciences

    Beijing, China

    3 h-index

    5 publications

    366 citations

1–8 of 348

Venues

  1. arXiv (Cornell University)

    Repository · 37 publications · 3.1K citations

    21

    h-index

  2. IEEE Access

    11 publications · 678 citations

    10

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 6 publications · 865 citations

    6

    h-index

  4. Applied Sciences

    6 publications · 259 citations

    6

    h-index

  5. Sensors

    5 publications · 283 citations

    5

    h-index

1–5