Convolutional neural network as a novel classification approach for laser-induced breakdown spectroscopy applications in lithological recognition

dc.contributor.author	Chen, J.
dc.contributor.author	Pisonero Castro, Jorge
dc.contributor.author	Chen, S.
dc.contributor.author	Wang, X.
dc.contributor.author	Fan, Q.
dc.contributor.author	Duan, Y.
dc.date.accessioned	2020-06-26T07:56:45Z
dc.date.available	2020-06-26T07:56:45Z
dc.date.issued	2020
dc.identifier.citation	Spectrochimica Acta - Part B Atomic Spectroscopy, 166, p. 105801- (2020); doi:10.1016/j.sab.2020.105801
dc.identifier.issn	0584-8547
dc.identifier.uri	http://hdl.handle.net/10651/55097
dc.description.sponsorship	The authors gratefully acknowledge the financial support from the National Major Scientific Instruments and Equipment Development Special Funds (No. 2011YQ030113)
dc.format.extent	p. 105801-
dc.language.iso	eng
dc.relation.ispartof	Spectrochimica Acta - Part B Atomic Spectroscopy
dc.rights	© 2020 Elsevier
dc.source	Scopus
dc.source.uri	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85080133872&doi=10.1016%2fj.sab.2020.105801&partnerID=40&md5=35d6ee1dcd40f4d6581a321f115a7745
dc.title	Convolutional neural network as a novel classification approach for laser-induced breakdown spectroscopy applications in lithological recognition
dc.type	journal article
dc.identifier.doi	10.1016/j.sab.2020.105801
dc.relation.publisherversion	http://dx.doi.org/10.1016/j.sab.2020.105801

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