A case study on visual-inertial odometry using supervised, semi-supervised and unsupervised learning methods

Yuan Tian, Marc Compere

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages203-207
Number of pages5
ISBN (Electronic)9781728156040
DOIs
StatePublished - Dec 2019
Externally publishedYes
Event2nd IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2019 - San Diego, United States
Duration: Dec 9 2019Dec 11 2019

Publication series

NameProceedings - 2019 IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2019

Conference

Conference2nd IEEE International Conference on Artificial Intelligence and Virtual Reality, AIVR 2019
Country/TerritoryUnited States
CitySan Diego
Period12/9/1912/11/19

ASJC Scopus Subject Areas

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Media Technology
  • Modeling and Simulation

Keywords

  • CNN-LSTM
  • Semi supervised
  • Supervised
  • Unsupervised
  • Visual Inertial Odometry

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