Abstract
In recent years, deep neural networks have reached state of the art performance across many different domains. Computer vision in particular has benefited immensely from deep learning. Despite their high performance, deep neural networks often lack interpretability and are mostly regarded as a black box. Therefore, the availability of tools capable to provide insights into the models and identify potential errors is crucial. Such tools need to seamlessly integrate within the workflow of data scientists and ML researchers. In this paper we propose iNNvestigate-GUI, an open-source graphical toolbox which offers an extensive set of functionalities for users to compare different networks behavior and give an explanation to their outputs.
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Notes
- 1.
Code is available at https://gitlab.com/grains2/innvestigate-gui/.
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Garcea, F., Famouri, S., Valentino, D., Morra, L., Lamberti, F. (2020). iNNvestigate-GUI - Explaining Neural Networks Through an Interactive Visualization Tool. In: Schilling, FP., Stadelmann, T. (eds) Artificial Neural Networks in Pattern Recognition. ANNPR 2020. Lecture Notes in Computer Science(), vol 12294. Springer, Cham. https://doi.org/10.1007/978-3-030-58309-5_24
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