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dc.contributor.authorChang, Julie
dc.contributor.authorSitzmann, Vincent
dc.contributor.authorDun, Xiong
dc.contributor.authorHeidrich, Wolfgang
dc.contributor.authorWetzstein, Gordon
dc.date.accessioned2021-01-20T12:28:38Z
dc.date.available2021-01-20T12:28:38Z
dc.date.issued2018-08-07
dc.identifier.urihttp://hdl.handle.net/10754/666954
dc.description.abstracthybrid optical electronic convolutional neural networks
dc.publisherGithub
dc.relation.urlhttps://github.com/computational-imaging/opticalCNN
dc.titlecomputational-imaging/opticalCNN: hybrid optical electronic convolutional neural networks
dc.typeSoftware
dc.contributor.departmentComputational Imaging Group
dc.contributor.departmentComputer Science Program
dc.contributor.departmentComputer, Electrical and Mathematical Science and Engineering (CEMSE) Division
dc.contributor.departmentVisual Computing Center (VCC)
dc.contributor.institutionBioengineering Department, Stanford University, Stanford, CA, 94305, USA.
dc.contributor.institutionElectrical Engineering Department, Stanford University, Stanford, CA, 94305, USA.
kaust.personDun, Xiong
kaust.personHeidrich, Wolfgang
dc.relation.issupplementtoDOI:10.1038/s41598-018-30619-y
display.relations<b>Is Supplement To:</b><br/> <ul><li><i>[Article]</i> <br/> Chang J, Sitzmann V, Dun X, Heidrich W, Wetzstein G (2018) Hybrid optical-electronic convolutional neural networks with optimized diffractive optics for image classification. Scientific Reports 8. Available: http://dx.doi.org/10.1038/s41598-018-30619-y.. DOI: <a href="https://doi.org/10.1038/s41598-018-30619-y" >10.1038/s41598-018-30619-y</a> Handle: <a href="http://hdl.handle.net/10754/628483" >10754/628483</a></a></li></ul>
dc.identifier.githubcomputational-imaging/opticalCNN


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