Replicating noise in video : a comparison between physics-based and deep learning models for simulating noise
Algorithms that track objects in video following Newtonian physics can often be affected by noise in the data. Some types of noise might be hard or expensive to capture, so to be able to augment or generate a new data set from models replicating a certain type of noise can be useful. Recent research...
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| Format: | Others |
| Language: | English |
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KTH, Skolan för elektroteknik och datavetenskap (EECS)
2020
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-272110 |