Name
Abstract | ||
|---|---|---|
We experimentally evaluated the efficacy of various autonomous supervised classification techniques for detecting transient geophysical phenomena. We demonstrated methods of detecting volcanic plumes on the planetary satellites Io and Enceladus using spacecraft images from the Voyager, Galileo, New Horizons, and Cassini missions. We successfully detected 73-95% of known plumes in images from all four mission datasets. Additionally, we showed that the same techniques are applicable to differentiating geologic features, such as plumes and mountains, which exhibit similar appearances in images. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ICRA.2012.6224796 | 2012 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA) |
Keywords | Field | DocType |
support vector machines,decision trees,vectors,image classification,decision tree,support vector machine,galileo,volcanology,artificial satellites,voyager,feature extraction | Object detection,Satellite,Geophysical Phenomena,Volcano,Volcanology,Engineering,Enceladus,Astrobiology,Spacecraft,Voyager program | Conference |
Volume | Issue | ISSN |
2012 | 1 | 1050-4729 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yucong Lin | 1 | 35 | 2.41 |
| Melissa Bunte | 2 | 5 | 0.96 |
| Srikanth Saripalli | 3 | 564 | 60.11 |
| Ronald Greeley | 4 | 30 | 7.57 |