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Home / Proceedings / Proceedings of the AAAI Conference on Human Computation and Crowdsourcing

Interpretable Image Recognition with Hierarchical Prototypes

February 1, 2023

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Authors

Peter Hase,Chaofan Chen,Oscar Li,Cynthia Rudin

University of North Carolina Chapel Hill,Duke University,Duke University,Duke University


DOI:

10.1609/hcomp.v7i1.5265


Abstract:

Vision models are interpretable when they classify objects on the basis of features that a person can directly understand. Recently, methods relying on visual feature prototypes have been developed for this purpose. However, in contrast to how humans categorize objects, these approaches have not yet made use of any taxonomical organization of class labels. With such an approach, for instance, we may see why a chimpanzee is classified as a chimpanzee, but not why it was considered to be a primate or even an animal. In this work we introduce a model that uses hierarchically organized prototypes to classify objects at every level in a predefined taxonomy. Hence, we may find distinct explanations for the prediction an image receives at each level of the taxonomy. The hierarchical prototypes enable the model to perform another important task: interpretably classifying images from previously unseen classes at the level of the taxonomy to which they correctly relate, e.g. classifying a hand gun as a weapon, when the only weapons in the training data are rifles. With a subset of ImageNet, we test our model against its counterpart black-box model on two tasks: 1) classification of data from familiar classes, and 2) classification of data from previously unseen classes at the appropriate level in the taxonomy. We find that our model performs approximately as well as its counterpart black-box model while allowing for each classification to be interpreted.

Topics: HCOMP

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HOW TO CITE:

Peter Hase,Chaofan Chen,Oscar Li,Cynthia Rudin Interpretable Image Recognition with Hierarchical Prototypes Proceedings of the AAAI Conference on Human Computation and Crowdsourcing (2019) 32-40.

Peter Hase,Chaofan Chen,Oscar Li,Cynthia Rudin Interpretable Image Recognition with Hierarchical Prototypes HCOMP 2019, 32-40.

Peter Hase,Chaofan Chen,Oscar Li,Cynthia Rudin (2019). Interpretable Image Recognition with Hierarchical Prototypes. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 32-40.

Peter Hase,Chaofan Chen,Oscar Li,Cynthia Rudin. Interpretable Image Recognition with Hierarchical Prototypes. Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 2019 p.32-40.

Peter Hase,Chaofan Chen,Oscar Li,Cynthia Rudin. 2019. Interpretable Image Recognition with Hierarchical Prototypes. "Proceedings of the AAAI Conference on Human Computation and Crowdsourcing". 32-40.

Peter Hase,Chaofan Chen,Oscar Li,Cynthia Rudin. (2019) "Interpretable Image Recognition with Hierarchical Prototypes", Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, p.32-40

Peter Hase,Chaofan Chen,Oscar Li,Cynthia Rudin, "Interpretable Image Recognition with Hierarchical Prototypes", HCOMP, p.32-40, 2019.

Peter Hase,Chaofan Chen,Oscar Li,Cynthia Rudin. "Interpretable Image Recognition with Hierarchical Prototypes". Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, 2019, p.32-40.

Peter Hase,Chaofan Chen,Oscar Li,Cynthia Rudin. "Interpretable Image Recognition with Hierarchical Prototypes". Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, (2019): 32-40.

Peter Hase,Chaofan Chen,Oscar Li,Cynthia Rudin. Interpretable Image Recognition with Hierarchical Prototypes. HCOMP[Internet]. 2019[cited 2023]; 32-40.


ISSN: 2769-1349


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