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Five years after the Deep Learning revolution of computer vision: State of the art methods for online image and video analysis
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0002-6096-3648
2017 (English)Report (Other academic)
Abstract [en]

The purpose of this document is to reect on novel and upcoming methods for computer vision that might have relevance for application in robot vision and video analytics. The document covers many dierent sub-elds of computer vision, most of which have been addressed by our research activity at the computer vision laboratory. The report has been written based on a request of, and supported by, FOI.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2017. , p. 13
National Category
Computer Vision and Robotics (Autonomous Systems) Computer Sciences Human Computer Interaction
Identifiers
URN: urn:nbn:se:liu:diva-143676OAI: oai:DiVA.org:liu-143676DiVA, id: diva2:1165440
Available from: 2017-12-13 Created: 2017-12-13 Last updated: 2018-01-13

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Five years after the Deep Learning revolution of computer vision: State of the art methods for online image and video analysis(326 kB)149 downloads
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Type fulltextMimetype application/pdf

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CiteExportLink to record
Permanent link

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Citation style
  • apa
  • ieee
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  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf