Interactive Visualization and Representation Analysis Applied to Glacier Segmentation
Computer Vision and Pattern Recognition
2022-03-14 v2 Machine Learning
Abstract
Interpretability has attracted increasing attention in earth observation problems. We apply interactive visualization and representation analysis to guide interpretation of glacier segmentation models. We visualize the activations from a U-Net to understand and evaluate the model performance. We build an online interface using the Shiny R package to provide comprehensive error analysis of the predictions. Users can interact with the panels and discover model failure modes. Further, we discuss how visualization can provide sanity checks during data preprocessing and model training.
Cite
@article{arxiv.2112.08184,
title = {Interactive Visualization and Representation Analysis Applied to Glacier Segmentation},
author = {Minxing Zheng and Xinran Miao and Kris Sankaran},
journal= {arXiv preprint arXiv:2112.08184},
year = {2022}
}
Comments
10 pages, 10 figures