A Supervised Approach to Predicting Noise in Depth Images
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers (IEEE)
2021
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Online Access: | https://hdl.handle.net/1721.1/137637 |
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author | Sweeney, Chris Izatt, Greg Tedrake, Russ |
author_facet | Sweeney, Chris Izatt, Greg Tedrake, Russ |
author_sort | Sweeney, Chris |
collection | MIT |
first_indexed | 2024-09-23T11:06:01Z |
format | Article |
id | mit-1721.1/137637 |
institution | Massachusetts Institute of Technology |
language | English |
last_indexed | 2024-09-23T11:06:01Z |
publishDate | 2021 |
publisher | Institute of Electrical and Electronics Engineers (IEEE) |
record_format | dspace |
spelling | mit-1721.1/1376372021-11-09T03:27:22Z A Supervised Approach to Predicting Noise in Depth Images Sweeney, Chris Izatt, Greg Tedrake, Russ 2021-11-08T12:51:01Z 2021-11-08T12:51:01Z 2019-05 2021-01-27T17:44:16Z Article http://purl.org/eprint/type/ConferencePaper https://hdl.handle.net/1721.1/137637 Sweeney, Chris, Izatt, Greg and Tedrake, Russ. 2019. "A Supervised Approach to Predicting Noise in Depth Images." 2019 International Conference on Robotics and Automation (ICRA). en 10.1109/ICRA.2019.8793820 2019 International Conference on Robotics and Automation (ICRA) Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Institute of Electrical and Electronics Engineers (IEEE) MIT web domain |
spellingShingle | Sweeney, Chris Izatt, Greg Tedrake, Russ A Supervised Approach to Predicting Noise in Depth Images |
title | A Supervised Approach to Predicting Noise in Depth Images |
title_full | A Supervised Approach to Predicting Noise in Depth Images |
title_fullStr | A Supervised Approach to Predicting Noise in Depth Images |
title_full_unstemmed | A Supervised Approach to Predicting Noise in Depth Images |
title_short | A Supervised Approach to Predicting Noise in Depth Images |
title_sort | supervised approach to predicting noise in depth images |
url | https://hdl.handle.net/1721.1/137637 |
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