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Signal Reconstruction Performance under Quantized Noisy Compressed Sensing
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-6096-3648
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering. Incept Inst Artificial Intelligence, U Arab Emirates.
2018 (English)In: 2019 DATA COMPRESSION CONFERENCE (DCC), IEEE , 2018, p. 149-155Conference paper, Published paper (Refereed)
Abstract [en]

n/a

Place, publisher, year, edition, pages
IEEE , 2018. p. 149-155
Keywords [en]
position estimation; horizon; registration; CNN; DEM
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
URN: urn:nbn:se:liu:diva-158889DOI: 10.1109/IPAS.2018.8708868ISI: 000471844500026ISBN: 978-1-7281-0247-4 (electronic)ISBN: 978-1-7281-0248-1 (print)OAI: oai:DiVA.org:liu-158889DiVA, id: diva2:1337524
Conference
3rd IEEE International Conference on Image Processing, Applications and Systems (IPAS)
Available from: 2019-07-15 Created: 2019-07-15 Last updated: 2019-07-17

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Grelsson, BertilRobinson, AndreasFelsberg, MichaelKhan, Fahad
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Citation style
  • apa
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  • de-DE
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  • nn-NB
  • sv-SE
  • Other locale
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Output format
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