Bibliographic Details
| Title: |
Blending Machine Learning and Interaction Design in Audio Explorer. |
| Authors: |
Scruggs, Colin1 (AUTHOR), Henkel, Cameron2 (AUTHOR), Stolper, Charles3 (AUTHOR), Cook, Kris4 (AUTHOR), Crouser, R. Jordan5 (AUTHOR) |
| Source: |
IEEE Computer Graphics & Applications. Mar/Apr2021, Vol. 41 Issue 2, p89-95. 7p. |
| Subjects: |
Microsoft Internet explorer (Computer software), Machine learning, Data visualization, Explorers, Task analysis |
| 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. [ABSTRACT FROM AUTHOR] |
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| Database: |
Engineering Source |
