Deep learning for digital holographic microscopy: Automatic detection of phase objects in raw holograms
Optics InfoBase Conference Papers, ISSN: 2162-2701
2020
- 1Citations
- 3Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Conference Paper Description
A method to automatically detect phase objects in DHM is presented. While traditional procedures require a reconstruction stage, our proposal processes the raw holograms with no reconstruction by using a CNN.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85165849372&origin=inward; http://dx.doi.org/10.1364/dh.2020.htu4b.3; https://opg.optica.org/abstract.cfm?URI=DH-2020-HTu4B.3; https://opg.optica.org/abstract.cfm?uri=DH-2020-HTu4B.3#videoPlayer; http://dx.doi.org/10.1364/dh.2020.htu4b.3.v001; https://dx.doi.org/10.1364/dh.2020.htu4b.3
Optica Publishing Group
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