Enhanced Bayesian Network Models for Spatial Time Series Prediction, Monidipa Das; Soumya K. Ghosh

Автор: Henning M?ller; B. Michael Kelm; Tal Arbel; Weidon
Название: Medical Computer Vision and Bayesian and Graphical Models for Biomedical Imaging
ISBN: 3319611879 ISBN-13(EAN): 9783319611877
Издательство: Springer
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Цена: 51230.00 T
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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
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Цена: 37270.00 T
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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: Enrique Castillo; Jose M. Gutierrez; Ali S. Hadi
Название: Expert Systems and Probabilistic Network Models
ISBN: 1461274818 ISBN-13(EAN): 9781461274810
Издательство: Springer
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Цена: 111790.00 T
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Описание: Artificial intelligence and expert systems have seen a great deal of research in recent years, much of which has been devoted to methods for incorporating uncertainty into models. This book is devoted to providing a thorough and up-to-date survey of this field for researchers and students.

Автор: Soto Jesus, Melin Patricia, Castillo Oscar
Название: Ensembles of Type 2 Fuzzy Neural Models and Their Optimization with Bio-Inspired Algorithms for Time Series Prediction
ISBN: 3319712632 ISBN-13(EAN): 9783319712635
Издательство: Springer
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Цена: 46570.00 T
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Описание: This book focuses on the fields of hybrid intelligent systems based on fuzzy systems, neural networks, bio-inspired algorithms and time series. Prediction errors are evaluated by the following metrics: Mean Absolute Error, Mean Square Error, Root Mean Square Error, Mean Percentage Error and Mean Absolute Percentage Error.

Автор: Nielsen Aileen
Название: Practical Time Series Analysis: Prediction with Statistics and Machine Learning
ISBN: 1492041653 ISBN-13(EAN): 9781492041658
Издательство: Wiley
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Цена: 67570.00 T
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Описание: Covering innovations in time series data analysis and use cases from the real world, this practical guide will help you solve the most common data engineering and analysis challenges in time series, using both traditional statistical and modern machine learning techniques.

Автор: Amit Konar; Diptendu Bhattacharya
Название: Time-Series Prediction and Applications
ISBN: 3319545965 ISBN-13(EAN): 9783319545967
Издательство: Springer
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Цена: 139750.00 T
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Описание: This book presents machine learning and type-2 fuzzy sets for the prediction of time-series with a particular focus on business forecasting applications.

Автор: Pole, Andy , West, Mike , Harrison, Jeff
Название: Applied Bayesian Forecasting and Time Series Analysis
ISBN: 0367449382 ISBN-13(EAN): 9780367449384
Издательство: Taylor&Francis
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Цена: 63280.00 T
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Описание: This book is about practical forecasting and analysis of time series. It describes how to analyse time series data, how to identify structure, how to explain observed behaviour, how to model structures and behaviours, and how to use insight gained from the analysis to make informed forecasts.

Автор: A. Ravishankar Rao; Guillermo A. Cecchi
Название: The Relevance of the Time Domain to Neural Network Models
ISBN: 1461429927 ISBN-13(EAN): 9781461429920
Издательство: Springer
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Цена: 174130.00 T
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Описание: Here is a unified view of how the time domain can be effectively employed in neural network models. Covers synchronization, phase-locking behavior, image processing, temporal pattern analysis, fMRI analyis, network topology and synchronizability and more.

Автор: BALL
Название: NETWORK MODELS HORM 7
ISBN: 0444892923 ISBN-13(EAN): 9780444892928
Издательство: Elsevier Science
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Цена: 53990.00 T
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Описание: This text presents papers reflecting the wide range of theories and applications of network models. Several chapters model issues in the domains of telecommunications and transportation.

Автор: Jan Treur
Название: Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models
ISBN: 3030314448 ISBN-13(EAN): 9783030314446
Издательство: Springer
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Цена: 93160.00 T
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Описание: Moreover, because adaptive networks are described in a network format as well, the approach can simply be applied iteratively, so that higher-order adaptive networks in which network adaptation itself is adaptive (second-order adaptation), too can be modeled just as easily.

Автор: Mehmet Eren Ahsen; Hitay ?zbay; Silviu-Iulian Nicu
Название: Analysis of Deterministic Cyclic Gene Regulatory Network Models with Delays
ISBN: 3319156055 ISBN-13(EAN): 9783319156057
Издательство: Springer
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Цена: 51230.00 T
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Описание: This brief examines a deterministic, ODE-based model for gene regulatory networks (GRN) that incorporates nonlinearities and time-delayed feedback. One chapter is devoted to the analysis of GRNs under negative feedback with time delays and a special case of a homogenous GRN is considered.

Автор: Gianni A. Di Caro; Guy Theraulaz
Название: Bio-Inspired Models of Network, Information, and Computing Systems
ISBN: 3319069438 ISBN-13(EAN): 9783319069432
Издательство: Springer
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Цена: 52170.00 T
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Описание: This book constitutes the thoroughly refereed post-conference proceedings of the 7th International Conference on Bio-Inspired Models of Network, Information and Computing Systems (Bionetics 2012), held in Lugano, Switzerland, in December 2012.