Global Explanations for Image Classifiers (Student Abstract)

Authors

  • Bhavan K. Vasu Oregon State University
  • Prasad Tadepalli Oregon State Unveristy

DOI:

https://doi.org/10.1609/aaai.v37i13.27036

Keywords:

Deep Neural Network, Explainable Artificial Intelligence, Interpretable Machine Learning, Model Interpretability, Scene Understanding, Deep Convolution Neural Network

Abstract

We hypothesize that deep network classifications of complex scenes can be explained using sets of relevant objects. We employ beam search and singular value decomposition to generate local and global explanations that summarize the deep model's interpretation of a class.
AAAI-23 Proceedings Cover

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Published

2023-09-06

How to Cite

Vasu, B. K., & Tadepalli, P. (2023). Global Explanations for Image Classifiers (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 37(13), 16352-16353. https://doi.org/10.1609/aaai.v37i13.27036

Issue

Vol. 37 No. 13: AAAI-23 Special Programs, IAAI-23, EAAI-23, Student Papers and Demonstrations

Section

AAAI Student Abstract and Poster Program