Främling, K., Knapic̆, S. and Malhi, A., 2021. ciu.image: An R Package for Explaining Image Classification with Contextual Importance and Utility. In: EXTRAAMAS 2021: Third International Workshop on Explainable, Transparent Autonomous Agents and Multi-Agent Systems, 3-7 May 2021, Virtual, 55 - 62.
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DOI: 10.1007/978-3-030-82017-6_4
Abstract
Many techniques have been proposed in recent years that attempt to explain results of image classifiers, notably for the case when the classifier is a deep neural network. This paper presents an implementation of the Contextual Importance and Utility method for explaining image classifications. It is an R package that can be used with the most usual image classification models. The paper shows results for typical benchmark images, as well as for a medical data set of gastro-enterological images. For comparison, results produced by the LIME method are included. Results show that CIU produces similar or better results than LIME with significantly shorter calculation times. However, the main purpose of this paper is to bring the existence of this package to general knowledge and use, rather than comparing with other explanation methods.
Item Type: | Conference or Workshop Item (Paper) |
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ISSN: | 0302-9743 |
Additional Information: | The work is partially supported by the Wallenberg AI, Autonomous Systems and Software Program (WASP) funded by the Knut and Alice Wallenberg Foundation. |
Uncontrolled Keywords: | Explainable Artificial Intelligence; Contextual Importance and Utility; Image Classification; Deep Neural Network |
Group: | Faculty of Science & Technology |
ID Code: | 36357 |
Deposited By: | Symplectic RT2 |
Deposited On: | 13 Dec 2021 10:48 |
Last Modified: | 14 Mar 2022 14:31 |
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