Classifier-Agnostic Saliency Map Extraction

Authors

  • Konrad Zołna Jagiellonian University
  • Krzysztof J. Geras New York University
  • Kyunghyun Cho Jagiellonian University

DOI:

https://doi.org/10.1609/aaai.v33i01.330110087

Abstract

Extracting saliency maps, which indicate parts of the image important to classification, requires many tricks to achieve satisfactory performance when using classifier-dependent methods. Instead, we propose classifier-agnostic saliency map extraction. This allows to find all parts of the image that any classifier could use, not just one given in advance. This way we extract much higher quality saliency maps.

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Published

2019-07-17

How to Cite

Zołna, K., Geras, K. J., & Cho, K. (2019). Classifier-Agnostic Saliency Map Extraction. Proceedings of the AAAI Conference on Artificial Intelligence, 33(01), 10087-10088. https://doi.org/10.1609/aaai.v33i01.330110087

Issue

Section

Student Abstract Track