Автор: Michael L. Mains; Brandon J. Dilworth Название: Topics in Modal Analysis & Testing, Volume 8 ISBN: 3030126838 ISBN-13(EAN): 9783030126834 Издательство: Springer Рейтинг: Цена: 27950.00 р. Наличие на складе: Поставка под заказ.
Описание: Topics in Modal Analysis & Testing, Volume 8: Proceedings of the 37th IMAC, A Conference and Exposition on Structural Dynamics, 2019, the eighth volume of eight from the Conference brings together contributions to this important area of research and engineering. The collection presents early findings and case studies on fundamental and applied aspects of Modal Analysis, including papers on: Analytical MethodsModal ApplicationsBasics of Modal AnalysisExperimental TechniquesMulti Degree of Freedom TestingBoundary Conditions in Environmental TestingOperational Modal AnalysisModal Parameter IdentificationNovel Techniques
Описание: This book presents the proceedings of the 2020 International Conference on Intelligent Systems Applications in Multi-modal Information Analytics, held in Changzhou, China, on June 18-19, 2020.
Описание: Specifically, it addresses a number of broad themes, including multi-modal informatics, data mining, agent-based and multi-agent systems for health and education informatics, which inspire the development of intelligent information technologies.
Описание: Specifically, it addresses a number of broad themes, including multi-modal informatics, data mining, agent-based and multi-agent systems for health and education informatics, which inspire the development of intelligent information technologies.
Описание: This book presents the proceedings of the 2019 International Conference on Intelligent Systems Applications in Multi-modal Information Analytics, held in Shenyang, China on February 19-20, 2019. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including data mining, multi-modal informatics, agent-based and multi-agent systems for health and education informatics, which inspire the development of intelligent information technologies. The contributions cover a wide range of topics: AI applications and innovations in health and education informatics; data and knowledge management; multi-modal application management; and web/social media mining for multi-modal informatics. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals, and provides a useful reference guide for newcomers to the field.
Описание: Specifically, it addresses a number of broad themes, including multimodal informatics, data mining, agent-based and multi-agent systems for health and education informatics, which inspire the development of intelligent information technologies.
Описание: This book presents the proceedings of the 2020 International Conference on Intelligent Systems Applications in Multi-modal Information Analytics, held in Changzhou, China, on June 18-19, 2020.
Автор: Chabane Djeraba; Adel Lablack; Yassine Benabbas Название: Multi-Modal User Interactions in Controlled Environments ISBN: 1461426316 ISBN-13(EAN): 9781461426318 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Investigating the capture and analysis of user`s multimodal behavior (mainly eye gaze, eye fixation, eye blink and body movements) within a real controlled environment, this text shows how the response of the computer or environment can be adapted to the user.
Автор: Heinrich Wansing Название: Displaying Modal Logic ISBN: 9048150795 ISBN-13(EAN): 9789048150793 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The present monograph is a slightly revised version of my Habilitations- schrift Proof-theoretic Aspects of Intensional and Non-Classical Logics, successfully defended at Leipzig University, November 1997.
Автор: Heinrich Wansing Название: Proof Theory of Modal Logic ISBN: 9048147204 ISBN-13(EAN): 9789048147205 Издательство: Springer Рейтинг: Цена: 27251.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Proof Theory of Modal Logic is devoted to a thorough study of proof systems for modal logics, that is, logics of necessity, possibility, knowledge, belief, time, computations etc. The volume is of immense importance for the interdisciplinary fields of logic, knowledge representation, and automated deduction.
Автор: Andrzej Indrzejczak Название: Natural Deduction, Hybrid Systems and Modal Logics ISBN: 9048187842 ISBN-13(EAN): 9789048187843 Издательство: Springer Рейтинг: Цена: 36197.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a detailed exposition of one of the most practical and popular methods of proving theorems in logic, called Natural Deduction.
Описание: ABCs - Anatomical Brain Barriers to Cancer Spread: Segmentation from CT and MR Images.- Cross-modality Brain Structures Image Segmentation for the Radiotherapy Target Definition and Plan Optimization.- Domain Knowledge Driven Multi-modal Segmentation of Anatomical Brain Barriers to Cancer Spread.- Ensembled ResUnet for Anatomical Brain Barriers Segmentation.- An Enhanced Coarse-to-_ne Framework for the segmentation of clinical target volume.- Automatic Segmentation of brain structures for treatment planning optimization and target volume definition.- A Bi-Directional, Multi-Modality Framework for Segmentation of Brain Structures.- L2R - Learn2Reg: Multitask and Multimodal 3D Medical Image Registration.- Large Deformation Image Registration with Anatomy-aware Laplacian Pyramid Networks.- Discrete Unsupervised 3D Registration Methods for the Learn2Reg Challenge.- Variable Fraunhofer MEVIS RegLib comprehensively applied to Learn2Reg Challenge.- Learning a deformable registration pyramid.- Deep learning based registration using spatial gradients and noisy segmentation labels.- Multi-step, Learning-based, Semi-supervised Image Registration Algorithm.- Using Elastix to register inhale/exhale intrasubject thorax CT: a unsupervised baseline to the task 2 of the Learn2Reg challenge.- TN-SCUI - Thyroid Nodule Segmentation and Classification in Ultrasound Images.- Cascade Unet and CH-Unet for thyroid nodule segmenation and benign and malignant classification.- Identifying Thyroid Nodules in Ultrasound Images through Segmentation-guided Discriminative Localization.- Cascaded Networks for Thyroid Nodule Diagnosis from Ultrasound Images.- Automatic Segmentation and Classification of Thyroid Nodules in Ultrasound Images with Convolutional Neural Networks.- LRTHR-Net: A Low-Resolution-to-High-Resolution Framework to Iteratively Refine the Segmentation of Thyroid Nodule in Ultrasound Images.- Coarse to Fine Ensemble Network for Thyroid Nodule Segmentation.
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