Publisher Correction: Non-invasive imaging through strongly scattering media based on speckle pattern estimation and deconvolution
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- ISSN
-
2045-2322
- Extent
-
Online-Ressource
- Language
-
Englisch
- Notes
-
online resource.
- Bibliographic citation
-
Publisher Correction: Non-invasive imaging through strongly scattering media based on speckle pattern estimation and deconvolution ; volume:8 ; number:1 ; day:5 ; month:7 ; year:2018 ; pages:1 ; date:12.2018
Scientific reports ; 8, Heft 1 (5.7.2018), 1, 12.2018
- Creator
-
Wang, Zhouping
- Contributor
-
Jin, Xin
Dai, Qionghai
SpringerLink (Online service)
- DOI
-
10.1038/s41598-018-28652-y
- URN
-
urn:nbn:de:101:1-2018091214150410003552
- Rights
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:39 AM CEST
Data provider
This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Wang, Zhouping
- Jin, Xin
- Dai, Qionghai
- SpringerLink (Online service)
Other Objects (12)
Non-invasive imaging through strongly scattering media based on speckle pattern estimation and deconvolution
Demographic Transition and Population Development in Belarus: Theory and Reality
The role of effort in understanding academic achievements: empirical evidence from China
Predicting academic success: machine learning analysis of student, parental, and school efforts
Macroeconomics with a Thick Pen
Misdiagnosis and Treatment of Corneal Complications Caused by Suture Exposure After Buried-Suture Double-Eyelid Blepharoplasty
Strong convergent result for quasi-nonexpansive mappings in Hilbert spaces
Disturbance rejection model predictive control of lower limb rehabilitation exoskeleton
Improving Topological Confinement Using Asymmetric Elements
Government governance, executive networks and enterprise R&D expenditure
Does the choice of realized covariance measures empirically matter? A Bayesian density prediction approach
Nanoscale switches for memorizing polymers
Non-invasive imaging through strongly scattering media based on speckle pattern estimation and deconvolution
Demographic Transition and Population Development in Belarus: Theory and Reality
The role of effort in understanding academic achievements: empirical evidence from China
Predicting academic success: machine learning analysis of student, parental, and school efforts
Macroeconomics with a Thick Pen
Misdiagnosis and Treatment of Corneal Complications Caused by Suture Exposure After Buried-Suture Double-Eyelid Blepharoplasty
Strong convergent result for quasi-nonexpansive mappings in Hilbert spaces
Disturbance rejection model predictive control of lower limb rehabilitation exoskeleton
Improving Topological Confinement Using Asymmetric Elements
Government governance, executive networks and enterprise R&D expenditure
Does the choice of realized covariance measures empirically matter? A Bayesian density prediction approach
Nanoscale switches for memorizing polymers
Non-invasive imaging through strongly scattering media based on speckle pattern estimation and deconvolution
Demographic Transition and Population Development in Belarus: Theory and Reality
The role of effort in understanding academic achievements: empirical evidence from China
Predicting academic success: machine learning analysis of student, parental, and school efforts
Macroeconomics with a Thick Pen
Misdiagnosis and Treatment of Corneal Complications Caused by Suture Exposure After Buried-Suture Double-Eyelid Blepharoplasty
Strong convergent result for quasi-nonexpansive mappings in Hilbert spaces
Disturbance rejection model predictive control of lower limb rehabilitation exoskeleton
Improving Topological Confinement Using Asymmetric Elements
Government governance, executive networks and enterprise R&D expenditure
Does the choice of realized covariance measures empirically matter? A Bayesian density prediction approach