01686nam0 22002891i 450 UON0009971220231205102547.48720020107d1984 |0itac50 baitaIT|||| 1||||Considerazioni sopra le cagioni della grandezza de' romani e della loro decadenzaTradotte dall'idioma franceseCharles Louis de Secondat MontesquieuNapoli : Istituto Universitario Orientale1984xxiii318 p. ; 23 cmRipr. facs. dell'ed. Venezia, 1785001UON000108012001 Collana "Matteo Ripa"2ITNapoliUONL000012MONTESQUIEUCharles Louis de Secondat : Baron deUONV064736646925Università degli Studi di Napoli "L'Orientale"UONV265274650ITSOL20241108RICAUON00099712SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI C 107 SI MC 8546 5 SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI COLL. FP 043 02 SI FP 232 7 SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI COLL. FP 043 02 bis SI 20883 7 bis SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI Francese IV A MON 05 SI LO 28894/2 5 05 BuonoConsiderazioni sopra le cagioni della grandezza de' romani e della loro decadenza1309737UNIOR03231nam 22007335 450 991034940710332120251225203803.09783030001292303000129610.1007/978-3-030-00129-2(CKB)4100000006519918(DE-He213)978-3-030-00129-2(MiAaPQ)EBC6298948(PPN)230538525(EXLCZ)99410000000651991820180911d2018 u| 0engurnn|008mamaatxtrdacontentcrdamediacrrdacarrierMachine Learning for Medical Image Reconstruction First International Workshop, MLMIR 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings /edited by Florian Knoll, Andreas Maier, Daniel Rueckert1st ed. 2018.Cham :Springer International Publishing :Imprint: Springer,2018.1 online resource (X, 158 p. 67 illus.) Image Processing, Computer Vision, Pattern Recognition, and Graphics,3004-9954 ;110749783030001285 3030001288 Includes bibliographical references and index.Deep learning for magnetic resonance imaging -- Deep learning for computed tomography -- Deep learning for general image reconstruction.This book constitutes the refereed proceedings of the First International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 17 full papers presented were carefully reviewed and selected from 21 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging; deep learning for computed tomography, and deep learning for general image reconstruction.Image Processing, Computer Vision, Pattern Recognition, and Graphics,3004-9954 ;11074Artificial intelligenceComputer visionComputer networksLogic designMedical informaticsArtificial IntelligenceComputer VisionComputer Communication NetworksLogic DesignHealth InformaticsArtificial intelligence.Computer vision.Computer networks.Logic design.Medical informatics.Artificial Intelligence.Computer Vision.Computer Communication Networks.Logic Design.Health Informatics.616.07540285006.31Knoll Florianedthttp://id.loc.gov/vocabulary/relators/edtMaier Andreasedthttp://id.loc.gov/vocabulary/relators/edtRueckert Danieledthttp://id.loc.gov/vocabulary/relators/edtMiAaPQMiAaPQMiAaPQBOOK9910349407103321Machine Learning for Medical Image Reconstruction1912511UNINA