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		<doi>10.1109/SIBGRAPI.2016.063</doi>
		<citationkey>HernándezSantTorr:2016:LeCoSp</citationkey>
		<title>Learning to Combine Spectral Indices with Genetic Programming</title>
		<format>On-line</format>
		<year>2016</year>
		<numberoffiles>1</numberoffiles>
		<size>1065 KiB</size>
		<author>Hernández, Juan Felipe,</author>
		<author>Santos, Jefersson Alex dos,</author>
		<author>Torres, Ricardo da S.,</author>
		<affiliation>Institute of Computing, University of Campinas</affiliation>
		<affiliation>Department of Computer Science, Federal University of Minas Gerais</affiliation>
		<affiliation>Institute of Computing, University of Campinas</affiliation>
		<editor>Aliaga, Daniel G.,</editor>
		<editor>Davis, Larry S.,</editor>
		<editor>Farias, Ricardo C.,</editor>
		<editor>Fernandes, Leandro A. F.,</editor>
		<editor>Gibson, Stuart J.,</editor>
		<editor>Giraldi, Gilson A.,</editor>
		<editor>Gois, João Paulo,</editor>
		<editor>Maciel, Anderson,</editor>
		<editor>Menotti, David,</editor>
		<editor>Miranda, Paulo A. V.,</editor>
		<editor>Musse, Soraia,</editor>
		<editor>Namikawa, Laercio,</editor>
		<editor>Pamplona, Mauricio,</editor>
		<editor>Papa, João Paulo,</editor>
		<editor>Santos, Jefersson dos,</editor>
		<editor>Schwartz, William Robson,</editor>
		<editor>Thomaz, Carlos E.,</editor>
		<e-mailaddress>juan.albarracin@students.ic.unicamp.br</e-mailaddress>
		<conferencename>Conference on Graphics, Patterns and Images, 29 (SIBGRAPI)</conferencename>
		<conferencelocation>São José dos Campos, SP, Brazil</conferencelocation>
		<date>4-7 Oct. 2016</date>
		<publisher>IEEE Computer Society´s Conference Publishing Services</publisher>
		<publisheraddress>Los Alamitos</publisheraddress>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Full Paper</tertiarytype>
		<transferableflag>1</transferableflag>
		<versiontype>finaldraft</versiontype>
		<keywords>Band selection and combination, Genetic Programming.</keywords>
		<abstract>This   paper   introduces   a   Genetic   Programming- based  method  for  band  selection  and  combination,  aiming  to support  remote  sensing  image  classification  tasks.  Relying  on ground-truth  data,  our  method  selects  spectral  bands  and  finds the  arithmetic  combination  of  those  bands  (i.e.,  spectral  index) that  best  separates  examples  of  different  classes.  Experimental results  demonstrate  that  the  proposed  method  is  very  effective in  pixel-wise  binary  classification  problems.</abstract>
		<language>en</language>
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		<usergroup>juan.albarracin@students.ic.unicamp.br</usergroup>
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