Applying Deep Learning To Improve Optimization- Based Approaches For Robust Sensor Fusion
Recent studies show that deep learning can be employed to learn from sensor data to improve accuracy and robustness of sensor fusion algorithms. In the same vein, in this thesis we use a state-of-the-art temporal convolution network to predict zero velocity updates (ZUPT) from raw inertial measureme...
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| Format: | Others |
| Language: | English |
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KTH, Skolan för elektroteknik och datavetenskap (EECS)
2021
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| Online Access: | http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-303253 |