Automating the Hunt for Volcanoes on Venus
Abstract
Our long-term goal is to develop a trainable tool for locating patterns of interest in large image databases. Toward this goal we have developed a prototype system, based on classical filtering and statistical pattern recognition techniques, for automatically locating volcanoes in the Magellan SAR database of Venus. Training for the specific volcano-detection task is obtained by synthesizing feature templates (via normalization and principal components analysis) from a small number of examples provided by experts. Candidate regions identified by a focus of attention (FOA) algorithm are classified based on correlations with the feature templates. Preliminary tests show performance comparable to trained human observers.
Cite
Text
Burl et al. "Automating the Hunt for Volcanoes on Venus." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1994. doi:10.1109/CVPR.1994.323844Markdown
[Burl et al. "Automating the Hunt for Volcanoes on Venus." IEEE/CVF Conference on Computer Vision and Pattern Recognition, 1994.](https://mlanthology.org/cvpr/1994/burl1994cvpr-automating/) doi:10.1109/CVPR.1994.323844BibTeX
@inproceedings{burl1994cvpr-automating,
title = {{Automating the Hunt for Volcanoes on Venus}},
author = {Burl, Michael C. and Fayyad, Usama M. and Perona, Pietro and Smyth, Padhraic},
booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition},
year = {1994},
pages = {302-309},
doi = {10.1109/CVPR.1994.323844},
url = {https://mlanthology.org/cvpr/1994/burl1994cvpr-automating/}
}