01521nam--2200409---450-99000267104020331620070131165823.0000267104USA01000267104(ALEPH)000267104USA0100026710420051012-1998----m||y0itay0103----baitaITy|||z|||001yy<<L'>> alfabetizzazione nelle scuole delal valle ladina di Fassacomparazione con i dati nazionali dell'indagine IEA-SAL e analisi longitudinaleGuido Benvenuto, Anna SalerniTrentoRotooffset Paganella1998106 p.24 cmStudi e ricercheSul front. : Provincia autonoma di Trento, IPRASE, Istituto porvinciale di ricerca aggiornamento sperimentazione educativiStudi e ricercheScuolaProfitto degli alunniValle ladina di FassaScuolaApprendimentoValle ladina di Fassa371.27BENVENUTO,Guido469014SALERNI,Anna573574ITUNIMARC990002671040203316II.4. 3098(VI B 923)182037 L.M.VI B00182285II.4. 3098a(VI B 952)182019 L.M.VI BBKUMAPAOLA9020051012USA011217COPAT19020051014USA011233COPAT69020070131USA011658Alfabetizzazione nelle scuole delal valle ladina di Fassa1002308UNISA02989nam 2200649 450 99631265030331620190920094934.03-11-040537-73-11-040548-210.1515/9783110405378(CKB)3710000000496990(EBL)4179750(SSID)ssj0001590242(PQKBManifestationID)16283972(PQKBTitleCode)TC0001590242(PQKBWorkID)14880241(PQKB)10659869(MiAaPQ)EBC4179750(DE-B1597)444551(OCoLC)979750999(DE-B1597)9783110405378(EXLCZ)99371000000049699020160111h20152015 uy 0gerur|n|---|||||txtccrKriegstagebuch einer jungen nationalsozialistin die aufzeichnungen Wolfhilde von Königs 1939-1946 /herausgegeben von Sven KellerBerlin, Germany ;Boston, [Massachusetts] :De Gruyter Oldenbourg,2015.©20151 online resource (266 p.)Schriftenreihe der Vierteljahrshefte für Zeitgeschichte,0506-9408 ;Band 11Description based upon print version of record.3-11-040538-5 3-11-040485-0 Includes bibliographical references and index.Frontmatter -- Inhalt -- I. Einleitung -- II. Kriegstagebuch -- Abkürzungen -- Abbildungen -- Bildquellen -- Quellen und Literatur -- PersonenregisterAls der Zweite Weltkrieg ausbrach, war Wolfhilde von König 13 Jahre alt. In den folgenden sieben Jahren führte sie ein "Kriegstagebuch". Die rund 630 Einträge dieses außerordentlichen Zeitzeugnisses dokumentieren sechs Jahre Krieg, die Zerstörung ihrer Heimatstadt München im Bombenkrieg, ihre Sorge um Vater und Bruder, die Niederlage, und die prekären ersten Nachkriegsmonate. Sie geben einen seltenen und unverstellten Blick in das Kriegserleben einer Jugendlichen und jungen Frau, die sich selbst als überzeugte Nationalsozialistin verstand. Ihre Selbstwahrnehmung, ihr Denken und ihr Alltag waren durch die Mitgliedschaft im Bund Deutscher Mädel und das begeisterte Engagement im Gesundheitsdienst des BDM geprägt.Schriftenreihe der Vierteljahrshefte für Zeitgeschichte ;Band 11.World War, 1939-1945Personal narratives, GermanMunich.National Socialism.Second World War.post-war period.World War, 1939-1945940.548243NQ 1760rvkKönig Wolfhilde von1925-1993,1246810Keller SvenMiAaPQMiAaPQMiAaPQBOOK996312650303316Kriegstagebuch einer jungen nationalsozialistin2890744UNISA06295nam 22007575 450 991074759120332120260706100603.09783031449178303144917710.1007/978-3-031-44917-8(MiAaPQ)EBC30775418(Au-PeEL)EBL30775418(DE-He213)978-3-031-44917-8(PPN)272913774(CKB)28477907800041(OCoLC)1402285499(EXLCZ)992847790780004120231007d2023 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMedical Image Learning with Limited and Noisy Data Second International Workshop, MILLanD 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, Proceedings /edited by Zhiyun Xue, Sameer Antani, Ghada Zamzmi, Feng Yang, Sivaramakrishnan Rajaraman, Sharon Xiaolei Huang, Marius George Linguraru, Zhaohui Liang1st ed. 2023.Cham :Springer Nature Switzerland :Imprint: Springer,2023.1 online resource (274 pages)Lecture Notes in Computer Science,1611-3349 ;14307Print version: Xue, Zhiyun Medical Image Learning with Limited and Noisy Data Cham : Springer,c2023 9783031471964 Efficient Annotation and Training Strategies -- Reducing Manual Annotation Costs for Cell Segmentation by Upgrading Low-quality Annotations -- ScribSD: Scribble-supervised Fetal MRI Segmentation based on Simultaneous Feature and Prediction Self-Distillation -- Label-efficient Contrastive Learning-based Model for Nuclei Detection and Classification in 3D Cardiovascular Immunofluorescent Images -- Affordable Graph Neural Network Framework using Topological Graph Contraction -- Approaches for Noisy, Missing, and Low Quality Data -- Dual-domain Iterative Network with Adaptive Data Consistency for Joint Denoising and Few-angle Reconstruction of Low-dose Cardiac SPECT -- A Multitask Framework for Label Refinement and Lesion Segmentation in Clinical Brain Imaging -- COVID-19 Lesion Segmentation Framework for the Contrast-enhanced CT in the Absence of Contrast-enhanced CT Annotation -- Feasibility of Universal Anomaly Detection without Knowingthe Abnormality in Medical Image -- Unsupervised, Self-supervised, and Contrastive Learning -- Decoupled Conditional Contrastive Learning with Variable Metadata for Prostate Lesion Detection -- FBA-Net: Foreground and Background Aware Contrastive Learning for Semi-Supervised Atrium Segmentation -- Masked Image Modeling for Label-Efficient Segmentation in Two-Photon Excitation Microscopy -- Automatic Quantification of COVID-19 Pulmonary Edema by Self-supervised Contrastive Learning -- SDLFormer: A Sparse and Dense Locality-enhanced Transformer for Accelerated MR Image Reconstruction -- Robust Unsupervised Image to Template Registration Without Image Similarity Los -- A Dual-Branch Network with Mixed and Self-Supervision for Medical Image Segmentation: An Application to Segment Edematous Adipose Tissue -- Weakly-supervised, Semi-supervised, and Multitask Learning -- Combining Weakly Supervised Segmentation with Multitask Learning forImproved 3D MRI Brain Tumour Classification -- Exigent Examiner and Mean Teacher: An Advanced 3D CNN-based Semi-Supervised Brain Tumor Segmentation Framework -- Extremely Weakly-supervised Blood Vessel Segmentation with Physiologically Based Synthesis and Domain Adaptation -- Multi-Task Learning for Few-Shot Differential Diagnosis of Breast Cancer Histopathology Image -- Active Learning -- Efficient Annotation for Medical Image Analysis: A One-Pass Selective Annotation Approach -- Test-time Augmentation-based Active Learning and Self-training for Label-efficient Segmentation -- Active Transfer Learning for 3D Hippocampus Segmentation -- Transfer Learning -- Using Training Samples as Transitive Information Bridges in Predicted 4D MRI -- To Pretrain or not to Pretrain? A Case Study of Domain-Specific Pretraining for Semantic Segmentation in Histopathology -- Large-scale Pretraining on Pathological Images for Fine-tuning of Small Pathological Benchmarks.This book consists of full papers presented in the 2nd workshop of ”Medical Image Learning with Noisy and Limited Data (MILLanD)” held in conjunction with the 26th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023). The 24 full papers presented were carefully reviewed and selected from 38 submissions. The conference focused on challenges and limitations of current deep learning methods applied to limited and noisy medical data and present new methods for training models using such imperfect data.Lecture Notes in Computer Science,1611-3349 ;14307Image processingDigital techniquesComputer visionComputer Imaging, Vision, Pattern Recognition and GraphicsImatges mèdiquesthubProcessament digital d'imatgesthubVisió per ordinadorthubReconeixement òptic de formesthubAprenentatge automàticthubCongressosthubLlibres electrònicsthubImage processingDigital techniques.Computer vision.Computer Imaging, Vision, Pattern Recognition and Graphics.Imatges mèdiquesProcessament digital d'imatgesVisió per ordinadorReconeixement òptic de formesAprenentatge automàtic006Xue Zhiyun1431715Antani Sameer1431716Zamzmi Ghada1431717Yang Feng871967Rajaraman Sivaramakrishnan1431718Huang Sharon Xiaolei1431719Linguraru Marius George1431720Liang Zhaohui1431721MiAaPQMiAaPQMiAaPQBOOK9910747591203321Medical Image Learning with Limited and Noisy Data3574626UNINA