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2023 8th International Conference on Robotics and Automation Engineering Quantifying the Performance of Deep Neural Networks in Predicting Curvature and Force Output Response of a Pneumatic Soft Actuator

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dc.contributor.authorLivinus, Ememobong N.
dc.contributor.authorGiannaccini, Maria Elena
dc.contributor.authorStarkey, Andrew
dc.contributor.authorAphale, Sumeet S.
dc.contributor.institutionUniversity of Aberdeen.Engineeringen
dc.contributor.institutionUniversity of Aberdeen.Engineeringen
dc.date.accessioned2024-08-01T23:12:29Z
dc.date.available2024-08-01T23:12:29Z
dc.date.embargoedUntil2024-08-02
dc.date.issued2024-03-14
dc.format.extent6
dc.format.extent782520
dc.identifier269839296
dc.identifiereb7b5a1c-22d2-4e92-954f-b15c80285a4e
dc.identifier85188552317
dc.identifier85188552317
dc.identifier.citationLivinus, E N, Giannaccini, M E, Starkey, A & Aphale, S S 2024, 2023 8th International Conference on Robotics and Automation Engineering Quantifying the Performance of Deep Neural Networks in Predicting Curvature and Force Output Response of a Pneumatic Soft Actuator. in 8th International Conference on Robotics and Automation Engineering (ICRAE 2023), November 17-19, Singapore.. Institute of Electrical and Electronics Engineers Inc., pp. 259-264, 8th International Conference on Robotics and Automation Engineering, ICRAE 2023, Singapore, Singapore, 17/11/23. https://doi.org/10.1109/ICRAE59816.2023.10458622en
dc.identifier.citationconferenceen
dc.identifier.doi10.1109/ICRAE59816.2023.10458622
dc.identifier.isbn9798350327656
dc.identifier.otherORCID: /0000-0002-1691-1648/work/160847268
dc.identifier.urihttps://hdl.handle.net/2164/23958
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85188552317&partnerID=8YFLogxKen
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.ispartof8th International Conference on Robotics and Automation Engineering (ICRAE 2023), November 17-19, Singapore.en
dc.subjectGRUen
dc.subjectLSTMen
dc.subjectPneumatic Soft Actuator (PSA)en
dc.subjectpredictionen
dc.subjectRNNen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectTK Electrical engineering. Electronics Nuclear engineeringen
dc.subjectArtificial Intelligenceen
dc.subjectControl and Systems Engineeringen
dc.subjectControl and Optimizationen
dc.subjectModelling and Simulationen
dc.subject.lccQA75en
dc.subject.lccTKen
dc.title2023 8th International Conference on Robotics and Automation Engineering Quantifying the Performance of Deep Neural Networks in Predicting Curvature and Force Output Response of a Pneumatic Soft Actuatoren
dc.typeConference itemen

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