Pantheon Institutional repository
Collect, preserve and disseminate digital academic production in all areas of knowledge.
Comprise the assets of the repository, in addition to theses and dissertations at UFRJ, scientific articles, electronic books, book chapters and papers presented at events for teachers, researchers, administrative staff and students of master's and doctoral degrees.
Browsing by Subject Traffic noise intensity
Showing results 1 to 1 of 1
| Author(s) | Title | Issue Date | Type |
|---|---|---|---|
| Mazza, Leonardo Oliveira | Sound pressure level prediction from video frames using deep convolutional neural networks | Jun-2019 | Dissertação |