LEADER 01606nam 2200469 450 001 9910616390203321 005 20231110212226.0 010 $a3-031-18576-5 035 $a(MiAaPQ)EBC7107727 035 $a(Au-PeEL)EBL7107727 035 $a(CKB)25048788800041 035 $a(PPN)265855594 035 $a(EXLCZ)9925048788800041 100 $a20230302d2022 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aDeep generative models $esecond MICCAI workshop, DGM4MICCAI 2022, held in conjunction with MICCAI 2022, Singapore, September 22, 2022, proceedings /$fedited by Anirban Mukhopadhyay [and four others] 210 1$aCham, Switzerland :$cSpringer,$d[2022] 210 4$dİ2022 215 $a1 online resource (136 pages) 225 1 $aLecture Notes in Computer Science ;$vv.13609 311 08$aPrint version: Mukhopadhyay, Anirban Deep Generative Models Cham : Springer,c2022 9783031185755 320 $aIncludes bibliographical references and index. 410 0$aLecture Notes in Computer Science 606 $aComputer vision 606 $aDeep learning (Machine learning) 606 $aComputer vision$vCongresses 615 0$aComputer vision. 615 0$aDeep learning (Machine learning) 615 0$aComputer vision 676 $a006.37 702 $aMukhopadhyay$b Anirban 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910616390203321 996 $aDeep generative models$93041715 997 $aUNINA