LEADER 01594nam0 22003371i 450 001 UON00274131 005 20231205103807.283 010 $a88-8265-361-7 100 $a20060307d2006 |0itac50 ba 101 $aita 102 $aIT 105 $a|||| ||||| 200 1 $aRilievi architettonici fittili d'etą imperiale dalla Campania$fGiuseppe Pellino 205 $aRoma : L'Erma$b2006 210 $a74 p.$d17 c. di tav.: ill. ; 29 cm 215 $aIn testa al front.: Ministero per i Beni e le Attivitą Culturali. Soprintendenza Archeologica di Pompei 316 $aSOPRINTENDENZA ARCHEOLOGICA DI POMPEI$5IT-UONSI N 2POMPEI042/13 410 1$1001UON00133793$12001 $aStudi della Soprintendenza Archeologica di Pompei$v13 606 $aTERRECOTTE ARCHITETTONICHE$xCollezioni$3UONC028661$2FI 606 $aDECORAZIONE ARCHITETTONICA$xCampania$xSec. 1. a.C.-5. d.C.$3UONC058686$2FI 606 $aRILIEVI FITTILI$xCollezioni$3UONC058687$2FI 620 $aIT$dRoma$3UONL000004 676 $a729.5$cDecorazione architettonica a rilievo$v21 700 1$aPELLINO$bGiuseppe$3UONV158931$0623477 712 $aL'Erma di Bretschneider$3UONV259640$4650 801 $aIT$bSOL$c20240220$gRICA 899 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$2UONSI 912 $aUON00274131 950 $aSIBA - SISTEMA BIBLIOTECARIO DI ATENEO$dSI N 2 POMPEI 042 13 $eSI MC 30025 7 13 SOPRINTENDENZA ARCHEOLOGICA DI POMPEI 996 $aRilievi architettonici fittili d'Etą Imperiale dalla Campania$91091037 997 $aUNIOR LEADER 02147nam0 22005173i 450 001 VAN00249047 005 20240806101417.86 017 70$2N$a9783030455293 100 $a20220804d2020 |0itac50 ba 101 $aeng 102 $aCH 105 $a|||| ||||| 200 1 $aDomain Adaptation in Computer Vision with Deep Learning$fHemanth Venkateswara, Sethuraman Panchanathan editors 210 $aCham$cSpringer$d2020 215 $axi, 256 p.$cill.$d24 cm 500 1$3VAN00249048$aDomain Adaptation in Computer Vision with Deep Learning$92310999 606 $a68-XX$xComputer science [MSC 2020]$3VANC019670$2MF 606 $a68Txx$xArtificial intelligence [MSC 2020]$3VANC021266$2MF 606 $a94-XX$xInformation and communication theory, circuits [MSC 2020]$3VANC019701$2MF 610 $aAdversarial learning$9KW:K 610 $aDeep Learning$9KW:K 610 $aDomain Confusion$9KW:K 610 $aDomain adaptation$9KW:K 610 $aDomain shift$9KW:K 610 $aFeature alignment$9KW:K 610 $aGenerative models$9KW:K 610 $aHashing$9KW:K 610 $aImage translation$9KW:K 610 $aLifelong Learning$9KW:K 610 $aMaximum mean discrepancy$9KW:K 610 $aMultitask Learning$9KW:K 610 $aSpectral methods$9KW:K 610 $aTransfer learning$9KW:K 610 $aZero-Shot Learning$9KW:K 620 $aCH$dCham$3VANL001889 702 1$aPanchanathan$bSethuraman$3VANV203794 702 1$aVenkateswara$bHemanth$3VANV203793 712 $aSpringer $3VANV108073$4650 801 $aIT$bSOL$c20241115$gRICA 856 4 $uhttp://doi.org/10.1007/978-3-030-45529-3$zE-book ? Accesso al full-text attraverso riconoscimento IP di Ateneo, proxy e/o Shibboleth 899 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$1IT-CE0120$2VAN08 912 $fN 912 $aVAN00249047 950 $aBIBLIOTECA DEL DIPARTIMENTO DI MATEMATICA E FISICA$d08DLOAD e-book 4632 $e08eMF4632 20220804 996 $aDomain Adaptation in Computer Vision with Deep Learning$92310999 997 $aUNICAMPANIA