Incremental learning of LSTM framework for sensor fusion in attitude estimation

This paper presents a novel method for attitude estimation of an object in 3D space by incremental learning of the Long-Short Term Memory (LSTM) network. Gyroscope, accelerometer, and magnetometer are few widely used sensors in attitude estimation applications. Traditionally, multi-sensor fusion met...

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Detalles Bibliográficos
Autores principales: Narkhede, Parag, Walambe, Rahee, Poddar, Shashi, Kotecha, Ketan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Artificial Intelligence
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356651/
https://www.ncbi.nlm.nih.gov/pubmed/34435103
http://dx.doi.org/10.7717/peerj-cs.662

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8356651/
https://www.ncbi.nlm.nih.gov/pubmed/34435103
http://dx.doi.org/10.7717/peerj-cs.662

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