http://rdf.ncbi.nlm.nih.gov/pubchem/reference/6003260
Outgoing Links
Predicate
Object
contentType
Proceedings Article
endingPage
259
issn
1063-6919
pageRange
251-259
publicationName
Proceedings. IEEE Computer Society Conference on Computer Vision and Pattern Recognition
startingPage
251
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bibliographicCitation
Zhang Z, Xing F, Shi X, Yang L. SemiContour: A Semi-supervised Learning Approach for Contour Detection. Proc IEEE Comput Soc Conf Comput Vis Pattern Recognit. 2016 Jun;2016():251–9. PMID: 28496297; PMCID: PMC5423734.
creator
http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_f1a3e40fd968ca5bd877ea4e1aec22d8
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http://rdf.ncbi.nlm.nih.gov/pubchem/author/MD5_f749cfdca0d90dd1b6d4e4932dc98ecc
date
201606
identifier
https://pubmed.ncbi.nlm.nih.gov/PMC5423734
https://doi.org/10.1109/cvpr.2016.34
https://pubmed.ncbi.nlm.nih.gov/28496297
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https://portal.issn.org/resource/ISSN/1063-6919
http://rdf.ncbi.nlm.nih.gov/pubchem/journal/35637
language
English
source
https://pubmed.ncbi.nlm.nih.gov/
https://www.crossref.org/
title
SemiContour: A Semi-Supervised Learning Approach for Contour Detection
Total number of triples:
23
.