Описание: Constructing Subject- and Disease-Specific Effect Maps: Application to Neurodegenerative Diseases.- BigBrain: Automated Cortical Parcellation and Comparison with Existing Brain Atlases.- LATEST: Local AdapTivE and Sequential Training for Tissue Segmentation of Isointense Infant Brain MR Images.- Landmark-based Alzheimer's Disease Diagnosis Using Longitudinal Structural MR Images.- Inferring Disease Status by non-Parametric Probabilistic Embedding.- A Lung Graph-Model for Pulmonary Hypertension and Pulmonary Embolism Detection on DECT Images.- Explaining Radiological Emphysema Subtypes with Unsupervised Texture Prototypes: MESA COPD Study.- Automatic Segmentation of Abdominal MRI Using Selective Sampling and Random Walker.- Gaze2Segment: A Pilot Study for Integrating Eye-Tracking Technology into Medical Image Segmentation.- Automatic Detection of Histological Artifacts in Mouse Brain Slice Images.- Lung Nodule Classification by Jointly Using Visual Descriptors and Deep Features.- Representation Learning for Cross-Modality Classification.- Guideline-based Machine Learning for Standard Plane Extraction in 3D Cardiac Ultrasound.- A Statistical Model for Simultaneous Template Estimation, Bias Correction, and Registration of 3D Brain Images.- Bayesian Multiview Manifold Learning Applied to Hippocampus Shape and Clinical Score Data.- Rigid Slice-To-Volume Medical Image Registration through Markov Random Fields.- Sparse Probabilistic Parallel Factor Analysis for the Modeling of PET and Task-fMRI data.- Non-local Graph-based Regularization for Deformable Image Registration.- Unsupervised Framework for Consistent Longitudinal MS Lesion Segmentation.
Автор: M. Jorge Cardoso; Ivor Simpson; Tal Arbel; Doina P Название: Bayesian and grAphical Models for Biomedical Imaging ISBN: 3319122886 ISBN-13(EAN): 9783319122885 Издательство: Springer Рейтинг: Цена: 5590.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
N3 Bias Field Correction Explained as a Bayesian Modeling Method.- A Bayesian Approach to Distinguishing Interdigitated Muscles in the Tongue from Limited Diffusion Weighted Imaging.- Optimal Joint Segmentation and Tracking of Escherichia Coli in the Mother Machine.- Physiologically Informed Bayesian Analysis of ASL fMRI Data.- Bone Reposition Planning for Corrective Surgery Using Statistical Shape Model: Assessment of Differential Geometrical Features.- An Inference Language for Imaging.- An MRF-Based Discrete Optimization Framework for Combined DCE-MRI Motion Correction and Pharmacokinetic Parameter Estimation.- Learning Imaging Biomarker Trajectories from Noisy Alzheimer's Disease Data Using a Bayesian Multilevel Model.- Four Neuroimaging Questions that P-Values Cannot Answer (and Bayesian Analysis Can).- Spherical Topic Models for Imaging Phenotype Discovery in Genetic Studies.- A Generative Model for Automatic Detection of Resolving Multiple Sclerosis Lesions.
Автор: Wainwright, Martin J Jordan, Michael I Название: Graphical models, exponential families, and variational inference ISBN: 1601981848 ISBN-13(EAN): 9781601981844 Издательство: Неизвестно Рейтинг: Цена: 17243.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Working with exponential family representations, and exploiting the conjugate duality between the cumulant function and the entropy for exponential families, this book develops general variational representations of the problems of computing likelihoods, marginal probabilities and most probable configurations.
Описание: This bookaims at promoting high-quality research by researchers and practitioners fromacademia and industry at the InternationalConference on Computational Intelligence, Cyber Security, and ComputationalModels ICC3 2015 organized by PSG College of Technology, Coimbatore, Indiaduring December 17 - 19, 2015.
Автор: Liu Название: Graphical Models for Security ISBN: 3319748599 ISBN-13(EAN): 9783319748597 Издательство: Springer Рейтинг: Цена: 5870.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book constitutes revised selected papers from the 4th International Workshop on Graphical Models for Security, GraMSec 2017, held in Santa Barbara, CA, USA, in August 2017. The 5 full and 4 short papers presented in this volume were carefully reviewed and selected from 19 submissions.
Автор: Jia Zeng; Zhi-Qiang Liu Название: Type-2 Fuzzy Graphical Models for Pattern Recognition ISBN: 3662515229 ISBN-13(EAN): 9783662515228 Издательство: Springer Рейтинг: Цена: 14365.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognition, topic modeling as well as human action recognition.
Автор: M.I. Jordan Название: Learning in Graphical Models ISBN: 9401061041 ISBN-13(EAN): 9789401061049 Издательство: Springer Рейтинг: Цена: 41925.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Proceedings of the NATO Advanced Study Institute, Ettore Maiorana Centre, Erice, Italy, September 27-October 7, 1996
Описание: Graphical models (e.g., Bayesian and constraint networks, influence diagrams, and Markov decision processes) have become a central paradigm for knowledge representation and reasoning in both artificial intelligence and computer science in general. These models are used to perform many reasoning tasks, such as scheduling, planning and learning, diagnosis and prediction, design, hardware and software verification, and bioinformatics. These problems can be stated as the formal tasks of constraint satisfaction and satisfiability, combinatorial optimization, and probabilistic inference. It is well known that the tasks are computationally hard, but research during the past three decades has yielded a variety of principles and techniques that significantly advanced the state of the art. This book provides comprehensive coverage of the primary exact algorithms for reasoning with such models. The main feature exploited by the algorithms is the model's graph. We present inference-based, message-passing schemes (e.g., variable-elimination) and search-based, conditioning schemes (e.g., cycle-cutset conditioning and AND/OR search). Each class possesses distinguished characteristics and in particular has different time vs. space behavior. We emphasize the dependence of both schemes on few graph parameters such as the treewidth, cycle-cutset, and (the pseudo-tree) height. The new edition includes the notion of influence diagrams, which focus on sequential decision making under uncertainty. We believe the principles outlined in the book would serve well in moving forward to approximation and anytime-based schemes. The target audience of this book is researchers and students in the artificial intelligence and machine learning area, and beyond.
Описание: Graphical models (e.g., Bayesian and constraint networks, influence diagrams, and Markov decision processes) have become a central paradigm for knowledge representation and reasoning in both artificial intelligence and computer science in general. These models are used to perform many reasoning tasks, such as scheduling, planning and learning, diagnosis and prediction, design, hardware and software verification, and bioinformatics. These problems can be stated as the formal tasks of constraint satisfaction and satisfiability, combinatorial optimization, and probabilistic inference. It is well known that the tasks are computationally hard, but research during the past three decades has yielded a variety of principles and techniques that significantly advanced the state of the art. This book provides comprehensive coverage of the primary exact algorithms for reasoning with such models. The main feature exploited by the algorithms is the model's graph. We present inference-based, message-passing schemes (e.g., variable-elimination) and search-based, conditioning schemes (e.g., cycle-cutset conditioning and AND/OR search). Each class possesses distinguished characteristics and in particular has different time vs. space behavior. We emphasize the dependence of both schemes on few graph parameters such as the treewidth, cycle-cutset, and (the pseudo-tree) height. The new edition includes the notion of influence diagrams, which focus on sequential decision making under uncertainty. We believe the principles outlined in the book would serve well in moving forward to approximation and anytime-based schemes. The target audience of this book is researchers and students in the artificial intelligence and machine learning area, and beyond.
Автор: G. Sai Sundara Krishnan; R. Anitha; R. S. Lekshmi; Название: Computational Intelligence, Cyber Security and Computational Models ISBN: 8132216792 ISBN-13(EAN): 9788132216797 Издательство: Springer Рейтинг: Цена: 39182.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book contains cutting-edge research material presented by researchers, engineers, developers, and practitioners from academia and industry at the International Conference on Computational Intelligence, Cyber Security and Computational Models (ICC3) organized by PSG College of Technology, Coimbatore, India during December 19-21, 2013.
Описание: This book constitutes the proceedings of the Third International Conference on Computational Intelligence, Cyber Security, and Computational Models, ICC3 2017, which was held in Coimbatore, India, in December 2017. They were organized in topical sections named: computational intelligence; and computational models.
Автор: Aboul Ella Hassanien; Mohamed Elhoseny; Syed Hassa Название: Security in Smart Cities: Models, Applications, and Challenges ISBN: 3030131858 ISBN-13(EAN): 9783030131852 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book offers an essential guide to IoT Security, Smart Cities, IoT Applications, etc. In addition, it presents a structured introduction to the subject of destination marketing and an exhaustive review on the challenges of information security in smart and intelligent applications, especially for IoT and big data contexts. Highlighting the latest research on security in smart cities, it addresses essential models, applications, and challenges.
Written in plain and straightforward language, the book offers a self-contained resource for readers with no prior background in the field. Primarily intended for students in Information Security and IoT applications (including smart cities systems and data heterogeneity), it will also greatly benefit academic researchers, IT professionals, policymakers and legislators. It is well suited as a reference book for both undergraduate and graduate courses on information security approaches, the Internet of Things, and real-world intelligent applications.
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