Name
Abstract | ||
|---|---|---|
The results of machine learning models can often be difficult to interpret, especially for domain experts. Audio Explorer, the winning entry of the 2018 VAST Challenge, is an interactive data exploration tool that effectively communicates machine learning results using coordinated geospatial, temporal, and auditory visualizations to promote information discovery. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/MCG.2019.2950185 | IEEE Computer Graphics and Applications |
Keywords | DocType | Volume |
audio classification,audio files,information discovery,machine learning models,auditory visualizations,temporal visualizations,coordinated geospatial visualizations,interactive data exploration tool,Audio Explorer | Journal | 41 |
Issue | ISSN | Citations |
2 | 0272-1716 | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Colin Scruggs | 1 | 0 | 0.34 |
| Cameron Henkel | 2 | 0 | 0.34 |
| Charles D. Stolper | 3 | 139 | 6.39 |
| Kristin Cook | 4 | 6 | 0.76 |
| Kristin A. Cook | 5 | 236 | 17.03 |