A Dashboard for Interactive Convolutional Neural Network Training And Validation Through Saliency Maps
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Date
2023
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
Quali-quantitative methods provide ways for interrogating Convolutional Neural Networks (CNN). For it, we propose a dashboard using a quali-quantitative method based on quantitative metrics and saliency maps. By those means, a user can discover patterns during the training of a CNN. With this, they can adapt the training hyperparameters of the model, obtaining a CNN that learned patterns desired by the user. Furthermore, they neglect CNNs which learned undesirable patterns. This improves users' agency over the model training process.
Description
CCS Concepts: Computing methodologies -> Artificial intelligence
@inproceedings{10.2312:evp.20231054,
booktitle = {EuroVis 2023 - Posters},
editor = {Gillmann, Christina and Krone, Michael and Lenti, Simone},
title = {{A Dashboard for Interactive Convolutional Neural Network Training And Validation Through Saliency Maps}},
author = {Cech, Tim and Simsek, Furkan and Scheibel, Willy and Döllner, Jürgen},
year = {2023},
publisher = {The Eurographics Association},
ISBN = {978-3-03868-220-2},
DOI = {10.2312/evp.20231054}
}