01183nam 2200385 450 991047996750332192-0-114819-4(CKB)3710000001364561(MiAaPQ)EBC4853270(EXLCZ)99371000000136456120170602h20152015 uy 0engurcnu||||||||rdacontentrdamediardacarrierNuclear power reactors in the world /International Atomic Energy Agency2015 edition.Vienna, [Austria] :International Atomic Energy Agency,2015.©20151 online resource (86 pages) illustrationsReference Data Series,1011-2642 ;Number 292-0-104915-3 Reference data series ;Number 2.Nuclear power plantsSafety measuresElectronic books.Nuclear power plantsSafety measures.621.4835MiAaPQMiAaPQMiAaPQBOOK9910479967503321Nuclear power reactors in the world1975487UNINA02818nam 22004695 450 99650067220331620231018213645.03-11-060486-810.1515/9783110604863(CKB)4100000007123574(MiAaPQ)EBC5574827(DE-B1597)496808(OCoLC)1078919110(DE-B1597)9783110604863(EXLCZ)99410000000712357420181207d2018 fg gerurcnu||||||||txtrdacontentcrdamediacrrdacarrierAkten zur Auswärtigen Politik der Bundesrepublik Deutschland Wissenschaftliche Leiterin: Ilse Dorothee Pautsch1961 /Mechthild Lindemann, Christoph Johannes Franzen3 TeilbdeBerlin ;Boston :De Gruyter,[2018]©20191 online resource (2,506 pages)Akten zur Auswärtigen Politik der Bundesrepublik Deutschland.3-11-060423-X Frontmatter --Inhalt --Vorwort --Vorbemerkungen zur Edition --Verzeichnisse --Dokumentenverzeichnis --Literaturverzeichnis --Abkürzungsverzeichnis --Dokumente --1- 24 --25 - 50 --51 - 68 --69 - 85 --86 - 108 --109 - 138 --139 - 160 --161 - 189 --190 - 216 --217 - 238 --239 - 262 --263 - 289 --290 - 320 --321 - 351 --352 - 386 --387 - 416 --417 - 442 --443 - 469 --470 - 499 --500 - 524 --525 - 550 --551 - 566 --Personenregister --Sachregister --Anhang: Organisationsplan des Auswärtigen Amts vom Juli 19611961 stand im Zeichen der Berlin-Krise, die mit dem Bau der Mauer ihren Höhepunkt fand. Zahlreiche der 566 Dokumente zeigen das Ringen der Bundesregierung mit den Alliierten um Maßnahmen gegen befürchtete weitere Sperrungen auf den Zugängen nach Berlin und um die eigene Rolle in der NATO. Im Fokus der Europapolitik standen Pläne für eine politische Union und einen britischen EWG-Beitritt. Der Eichmann-Prozess in Jerusalem verdeutlichte, wie sehr die Bonner Außenpolitik noch im Schatten der NS-Zeit stand. Die Konkurrenz mit der DDR in den jungen Staaten Afrikas beschleunigte den Ausbau der Entwicklungspolitik; die Zuständigkeit dafür fiel indes in zähen Koalitionsverhandlungen nach der Bundestagswahl vom 17. September an ein neues Ressort.DiplomacyGermany (West)Foreign relationsSourcesDiplomacy.327.43009045Franzen Christoph JohannesLindemann MechthildDE-B1597DE-B1597BOOK996500672203316Akten zur auswartigen Politik der Bundesrepublik Deutschland841624UNISA11021nam 22005413 450 99656586740331620231203090315.03-031-47401-5(MiAaPQ)EBC30980189(Au-PeEL)EBL30980189(EXLCZ)992912802620004120231203d2024 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMedical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops ISIC 2023, Care-AI 2023, MedAGI 2023, DeCaF 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8-12, 2023, Proceedings1st ed.Cham :Springer,2024.©2023.1 online resource (397 pages)Lecture Notes in Computer Science Series ;v.14393Print version: Celebi, M. Emre Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops Cham : Springer,c2024 9783031474002 Intro -- Workshop Editors -- ISIC Preface -- ISIC 2023 Organization -- Care-AI 2023 Preface -- Care-AI 2023 Organization -- MedAGI 2023 Preface -- MedAGI 2023 Organization -- DeCaF 2023 Preface -- DeCaF 2023 Organization -- Contents -- Proceedings of the Eighth International Skin Imaging Collaboration Workshop (ISIC 2023) -- Continual-GEN: Continual Group Ensembling for Domain-agnostic Skin Lesion Classification -- 1 Introduction -- 2 Continual-GEN -- 3 Experiments and Results -- 4 Conclusion -- References -- Communication-Efficient Federated Skin Lesion Classification with Generalizable Dataset Distillation -- 1 Introduction -- 2 Method -- 2.1 Generalizable Dataset Distillation -- 2.2 Distillation Process -- 2.3 Communication-Efficient Federated Learning -- 3 Experiment -- 3.1 Datasets and Evaluation Metrics -- 3.2 Implementation Details -- 3.3 Comparison of State-of-the-Arts -- 3.4 Detailed Analysis -- 4 Conclusion -- References -- AViT: Adapting Vision Transformers for Small Skin Lesion Segmentation Datasets -- 1 Introduction -- 2 Methodology -- 2.1 Basic ViT -- 2.2 AViT -- 3 Experiments -- 4 Conclusion -- References -- Test-Time Selection for Robust Skin Lesion Analysis -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Results -- 5 Conclusion -- References -- Global and Local Explanations for Skin Cancer Diagnosis Using Prototypes -- 1 Introduction -- 2 Proposed Approach -- 2.1 Clustering -- 2.2 Global Prototypes -- 2.3 Local Prototypes -- 2.4 Pruning and Final Classifier -- 2.5 Visual Explanations -- 3 Experimental Setup -- 4 Results -- 5 Conclusions -- References -- Evidence-Driven Differential Diagnosis of Malignant Melanoma -- 1 Introduction -- 2 Method -- 3 Experiments -- 3.1 Data -- 3.2 Experimental Settings -- 4 Results and Discussion -- 5 Conclusion -- References.Proceedings of the First Clinically-Oriented and Responsible AI for Medical Data Analysis (Care-AI 2023) Workshop -- An Interpretable Machine Learning Model with Deep Learning-Based Imaging Biomarkers for Diagnosis of Alzheimer's Disease -- 1 Introduction -- 2 Methods -- 2.1 Study Population -- 2.2 Data Preprocessing -- 2.3 Explainable Boosting Machine (EBM) -- 2.4 Proposed Extension -- 2.5 Extraction of the DL-Biomarkers -- 3 Experiments -- 3.1 Validation Study -- 3.2 EBM Using DL-Biomarkers -- 3.3 Baseline Methods -- 4 Results -- 4.1 Glo-CNN and ROIs -- 4.2 Comparison Study -- 5 Discussion and Conclusions -- References -- Generating Chinese Radiology Reports from X-Ray Images: A Public Dataset and an X-ray-to-Reports Generation Method -- 1 Introduction -- 2 Related Work -- 3 Datasets -- 3.1 CN-CXR Dataset -- 3.2 CN-RadGraph Dataset -- 4 Method -- 5 Results and Analysis -- 5.1 Pre-processing and Evaluation -- 5.2 Performance and Comparisons -- References -- Gradient Self-alignment in Private Deep Learning -- 1 Introduction -- 2 Background and Related Work -- 3 Methodology -- 3.1 DP-SGD with a Cosine Similarity Filter -- 3.2 DP-SGD with Dimension-Filtered Cosine Similarity Filter -- 4 Experiments and Discussion -- 4.1 Experimental Setup -- 4.2 Results and Discussion -- 5 Conclusion -- References -- Cellular Features Based Interpretable Network for Classifying Cell-Of-Origin from Whole Slide Images for Diffuse Large B-cell Lymphoma Patients -- 1 Introduction -- 2 Methodology -- 2.1 Nuclei Segmentation and Classification -- 2.2 Cellular Feature Extraction -- 2.3 AMIL Model Training -- 2.4 CellFiNet Interpretability -- 2.5 Benchmark Methods -- 3 Experiments and Results -- 3.1 Data -- 3.2 Results -- 4 Interpretability -- 5 Conclusion and Discussion -- References.Multimodal Learning for Improving Performance and Explainability of Chest X-Ray Classification -- 1 Introduction -- 2 Method -- 2.1 Classification Performance Experiments -- 2.2 Explainability Experiments -- 3 Results -- 3.1 Classification Performance Results -- 3.2 Explainability Results -- 4 Conclusion -- References -- Proceedings of the First International Workshop on Foundation Models for Medical Artificial General Intelligence (MedAGI 2023) -- Cross-Task Attention Network: Improving Multi-task Learning for Medical Imaging Applications -- 1 Introduction -- 2 Methods and Materials -- 2.1 Cross-Task Attention Network (CTAN) -- 2.2 Training Details -- 2.3 Evaluation -- 2.4 Datasets -- 3 Experiments and Results -- 4 Discussion -- References -- Input Augmentation with SAM: Boosting Medical Image Segmentation with Segmentation Foundation Model -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Segmentation and Boundary Prior Maps -- 3.2 Augmenting Input Images -- 3.3 Model Training with SAM-Augmented Images -- 3.4 Model Deployment with SAM-Augmented Images -- 4 Experiments and Results -- 4.1 Datasets and Setups -- 4.2 Polyp Segmentation on Five Datasets -- 4.3 Cell Segmentation on the MoNuSeg Dataset -- 4.4 Gland Segmentation on the GlaS Dataset -- 5 Conclusions -- References -- Empirical Analysis of a Segmentation Foundation Model in Prostate Imaging -- 1 Introduction -- 2 Related Works -- 2.1 UniverSeg -- 2.2 Prostate MR Segmentation -- 3 Experiments -- 3.1 Datasets -- 3.2 UniverSeg Inference -- 3.3 nnUNet -- 3.4 Empirical Evaluation -- 4 Results -- 4.1 Computational Resource -- 4.2 Segmentation Performance -- 4.3 Conclusion -- References -- GPT4MIA: Utilizing Generative Pre-trained Transformer (GPT-3) as a Plug-and-Play Transductive Model for Medical Image Analysis -- 1 Introduction -- 2 Approach -- 2.1 Theoretical Analyses.2.2 Prompt Construction -- 2.3 Workflow and Use Cases -- 3 Experiments -- 3.1 On Detecting Prediction Errors -- 3.2 On Improving Classification Accuracy -- 3.3 Ablation Studies -- 4 Discussion and Conclusions -- References -- SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology -- 1 Introduction -- 2 Method -- 2.1 Pathology Encoder -- 2.2 Class Prompts -- 2.3 Optimization -- 3 Experiments -- 3.1 Dataset -- 3.2 Results -- 4 Conclusion -- References -- Multi-task Cooperative Learning via Searching for Flat Minima -- 1 Introduction -- 2 Method -- 2.1 Bi-Level Optimization for Cooperative Two-Task Learning -- 2.2 Finding Flat Minima via Injecting Noise -- 3 Experiments -- 3.1 Dataset -- 3.2 Results on MNIST Dataset -- 3.3 Comparison on REFUGE2018 Dataset -- 3.4 Comparison on HRF-AV Dataset -- 4 Conclusion -- References -- MAP: Domain Generalization via Meta-Learning on Anatomy-Consistent Pseudo-Modalities -- 1 Introduction -- 2 Methods -- 2.1 Problem Definition -- 2.2 Pseudo-modality Synthesis -- 2.3 Meta-learning on Anatomy Consistent Image Space -- 2.4 Structural Correlation Constraints -- 2.5 Experimental Settings -- 3 Results -- 4 Conclusion -- References -- A General Computationally-Efficient 3D Reconstruction Pipeline for Multiple Images with Point Clouds -- 1 Introduction -- 2 Related Works -- 3 Method -- 4 Implementation -- 5 Quantitative Results -- 6 Conclusion and Future Work -- References -- GPC: Generative and General Pathology Image Classifier -- 1 Introduction -- 2 Methodology -- 2.1 Problem Formulation -- 2.2 Network Architecture -- 3 Experiments -- 3.1 Datasets -- 3.2 Comparative Models -- 3.3 Experimental Design -- 3.4 Training Details -- 3.5 Metrics -- 4 Results and Discussion -- 5 Conclusions -- References.Towards Foundation Models and Few-Shot Parameter-Efficient Fine-Tuning for Volumetric Organ Segmentation -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 4 Experiments -- 5 Conclusions -- References -- Concept Bottleneck with Visual Concept Filtering for Explainable Medical Image Classification -- 1 Introduction -- 2 Related Works -- 2.1 Concept Bottleneck Models -- 2.2 Large Language Models -- 3 Method -- 3.1 Preliminary -- 3.2 Concept Selection with Visual Activation Score -- 4 Experiments -- 4.1 Experimental Results -- 5 Analysis -- 5.1 Analysis on a Visual Activation Score V(c) -- 5.2 Analysis on Target Image Set X -- 5.3 Qualitative Examples -- 6 Conclusion -- References -- SAM Meets Robotic Surgery: An Empirical Study on Generalization, Robustness and Adaptation -- 1 Introduction -- 2 Experimental Settings -- 3 Surgical Instruments Segmentation with Prompts -- 4 Robustness Under Data Corruption -- 5 Automatic Surgical Scene Segmentation -- 6 Parameter-Efficient Finetuning with Low-Rank Adaptation -- 7 Conclusion -- References -- Evaluation and Improvement of Segment Anything Model for Interactive Histopathology Image Segmentation -- 1 Introduction -- 2 Method -- 2.1 Overview of Segment Anything Model (SAM) -- 2.2 SAM Fine-Tuning Scenarios -- 2.3 Decoder Architecture Modification -- 3 Experiments -- 3.1 Data Description -- 3.2 Implementation Details -- 4 Results -- 4.1 Zero-Shot Performance -- 4.2 Fine-Tuned SAM Performance -- 4.3 Comparison Between SAM and SOTA Interactive Methods -- 4.4 Modified SAM Decoder Performance -- 5 Conclusion -- References -- Task-Driven Prompt Evolution for Foundation Models -- 1 Introduction -- 1.1 Our Approach -- 1.2 Contributions -- 2 Methodology -- 2.1 Prompt Optimization by Oracle Scoring -- 2.2 Learning to Score -- 3 Experiments and Results -- 3.1 Dataset Description -- 3.2 Segmentation Regressor.3.3 Prompt Optimization.Lecture Notes in Computer Science SeriesCelebi M. Emre1448701Salekin Sirajus1448702Kim Hyunwoo1448703Albarqouni Shadi1448704Barata Catarina1301124Halpern Allan1448705Tschandl Philipp1434864Combalia Marc1448706Liu Yuan1415362Zamzmi Ghada1431717MiAaPQMiAaPQMiAaPQBOOK996565867403316Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops3644374UNISA01343nam0 22002891i 450 UON0010835620231205102625.27620020107d1979 |0itac50 baengSE|||| |||||Vasilike warean early bronze age pottery style in Creteresults of the Philadelphia vasilike ware projectby Philip P. Betancourtin collaboratiohn with Thomas K. Gaisser ... [et al.]GoteborgPaul Astroms Forlag197960 p., 8 p. di tav.31 cm001UON000873392001 Studies in Mediterranean Archaeologyedited by Paul Astrom56001UON003654872001 ˆAn ‰early bronze age pottery style in Crete001UON003654882001 Results of the philadelphia vasilike ware projectSEGoteborgUONL000682BETANCOURTPhilip P.UONV069109208786GAISSERThomas K.UONV069110Paul Astroms forlagUONV259975650ITSOL20240220RICASIBA - SISTEMA BIBLIOTECARIO DI ATENEOUONSIUON00108356SIBA - SISTEMA BIBLIOTECARIO DI ATENEOSI Per S 0350 056 1979 SI MC 3542 5 1979 Vasilike ware1307285UNIOR