Machine learning models for geospatial data

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Serval ID
serval:BIB_D8BE81C727EF
Type
A part of a book
Publication sub-type
Chapter: chapter ou part
Collection
Publications
Institution
UNIL/CHUV
Title
Machine learning models for geospatial data
Title of the book
Handbook of Theoretical and Quantitative Geography
Author(s)
Kanevski Mikhail, Foresti Loris, Kaiser Christian, Pozdnoukhov Alexei, Timonin Vadim, Tuia Devis
Publisher
University, Faculty of geosciences and environment
Address of publication
Lausanne
Publication state
Published
Issued date
2009
Editor
Bavaud François, Mager Christophe
Series
Workshop series
Pages
175-227
Language
english
Keywords
Machine learning, Quantitative Geography
OAI-PMH
oai:serval.unil.ch:BIB_D8BE81C727EF
Create date
01/08/2010 11:34
Last modification date
20/08/2019 15:58
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