LEADER 01227nam 2200409 450 001 9910466360603321 005 20200520144314.0 010 $a2-335-15577-6 035 $a(CKB)3820000000022880 035 $a(MiAaPQ)EBC4466192 035 $a(Au-PeEL)EBL4466192 035 $a(CaPaEBR)ebr11192643 035 $a(OCoLC)946009845 035 $a(EXLCZ)993820000000022880 100 $a20160515h20152015 uy 0 101 0 $afre 135 $aurcnu|||||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 13$aLa Fore?t vosgienne, son aspect, son histoire, ses le?gendes /$fHenry Bour 210 1$a[Place of publication not identified] :$cE?ditions Ligaran,$d2015. 210 4$dİ2015 215 $a1 online resource (37 pages) 300 $a"Livre nume?rique"--Cover. 606 $aForests and forestry$xHistory 608 $aElectronic books. 615 0$aForests and forestry$xHistory. 676 $a333.7509 700 $aBour$b Henry$0953524 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910466360603321 996 $aLa Fore?t vosgienne, son aspect, son histoire, ses le?gendes$92156043 997 $aUNINA LEADER 01752nam 2200361 450 001 9910688461703321 005 20230628221141.0 035 $a(CKB)5400000000043932 035 $a(NjHacI)995400000000043932 035 $a(EXLCZ)995400000000043932 100 $a20230628d2020 uy 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aProcessing and Analysis of Hyperspectral Data /$fJie Chen, Yingying Song, Hengchao Li 210 1$aLondon :$cIntechOpen,$d2020. 215 $a1 online resource (136 pages) 311 $a1-83880-462-5 330 $aHyperspectral imagery has received considerable attention in the last decade as it provides rich spectral information and allows the analysis of objects that are unidentifiable by traditional imaging techniques. It has a wide range of applications, including remote sensing, industry sorting, food analysis, biomedical imaging, etc. However, in contrast to RGB images from which information can be intuitively extracted, hyperspectral data is only useful with proper processing and analysis. This book covers theoretical advances of hyperspectral image processing and applications of hyperspectral processing, including unmixing, classification, super-resolution, and quality estimation with classical and deep learning methods. 606 $aSpectrum analysis 615 0$aSpectrum analysis. 676 $a535.84 700 $aChen$b Jie$01299851 702 $aSong$b Yingying 702 $aLi$b Hengchao 801 0$bNjHacI 801 1$bNjHacl 906 $aBOOK 912 $a9910688461703321 996 $aProcessing and Analysis of Hyperspectral Data$93394347 997 $aUNINA LEADER 00996nam0 2200301 i 450 001 BVE0048264 005 20231121125413.0 010 $a8806134620 020 $aIT$b94-3384 100 $a20181129d1994 ||||0itac50 ba 101 | $aita 102 $ait 181 1$6z01$ai $bxxxe 182 1$6z01$an 200 1 $aMarco e Mattio$fSebastiano Vassalli 210 $aTorino$cEinaudi$dİ1994 215 $a314 p.$d20 cm. 225 | $aEinaudi tascabili$v176 410 0$1001CFI0163201$12001 $aEinaudi tascabili$v176 700 1$aVassalli$b, Sebastiano$f <1941-2015>$3CFIV007958$4070$0153434 801 3$aIT$bIT-01$c20181129 850 $aIT-FR0017 899 $aBiblioteca umanistica Giorgio Aprea$bFR0017 $eN 912 $aBVE0048264 950 0$aBiblioteca umanistica Giorgio Aprea$d 52MAG 1/1704$e 52FLS0000287085 VMB RS $fA $h20181129$i20181129 977 $a 52 996 $aMarco e Mattio$9146742 997 $aUNICAS