Image Texture Analysis: Foundations, Models and Algorithms, Hung Chih-Cheng, Song Enmin, Lan Yihua
Автор: Lawrence O`Gorman Название: Practical Algorithms for Image Analysis with CD-ROM ISBN: 052188411X ISBN-13(EAN): 9780521884112 Издательство: Cambridge Academ Рейтинг: Цена: 8402.00 р. Наличие на складе: Поставка под заказ.
Описание: In classic `cookbook style`, this book offers guided access to a collection of algorithms for the digital manipulation and analysis of images, from the simplest steps to advanced functions. In this new edition, the accompanying CD-ROM contains C programs for carrying out the book`s procedures not only as source code but also as executables for Windows and Linux.
Автор: Hung Chih-Cheng Название: Image Texture Analysis ISBN: 3030137724 ISBN-13(EAN): 9783030137724 Издательство: Springer Рейтинг: Цена: 6567.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This useful textbook/reference presents an accessible primer on the fundamentals of image texture analysis, as well as an introduction to the K-views model for extracting and classifying image textures. describes the basics of image texture, texture features, and image texture classification and segmentation;
Автор: Michal Haindl; Jiri Filip Название: Visual Texture ISBN: 1447149017 ISBN-13(EAN): 9781447149019 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book surveys the state of the art in multidimensional, physically-correct visual texture modeling. The authors review the entire process of texture synthesis, visualization, measurement and analysis, as well as applications in medicine and industry.
Автор: Jyotismita Chaki; Nilanjan Dey Название: Texture Feature Extraction Techniques for Image Recognition ISBN: 9811508526 ISBN-13(EAN): 9789811508523 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book describes various texture feature extraction approaches and texture analysis applications. It introduces and discusses the importance of texture features, and describes various types of texture features like statistical, structural, signal-processed and model-based.
Автор: A. Ravishankar Rao Название: A Taxonomy for Texture Description and Identification ISBN: 1461397790 ISBN-13(EAN): 9781461397793 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The symbolic de- scription scheme consists of a novel taxonomy for textures, and is based on appropriate mathematical models for different kinds of texture. Disordered textures are described by statistical mea- sures, strongly ordered textures by the placement of primitives, and weakly ordered textures by an orientation field.
Автор: Fumiaki Tomita; Saburo Tsuji Название: Computer Analysis of Visual Textures ISBN: 1461288320 ISBN-13(EAN): 9781461288329 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book presents theories and techniques for perception of textures by computer. Texture analysis is one of the first important steps in computer vision since texture provides important cues to recognize real-world objects.
Автор: Georgy L. Gimel`farb Название: Image Textures and Gibbs Random Fields ISBN: 9401059128 ISBN-13(EAN): 9789401059121 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Image analysis is one of the most challenging areas in today`s computer sci- ence, and image technologies are used in a host of applications.
Описание: This is the first comprehensive treatment of subjective logic and all its operations. The author developed the approach, and in this book he first explains subjective opinions, opinion representation, and decision-making under vagueness and uncertainty, and he then offers a full definition of subjective logic, harmonising the key notations and formalisms, concluding with chapters on trust networks and subjective Bayesian networks, which when combined form general subjective networks. The author shows how real-world situations can be realistically modelled with regard to how situations are perceived, with conclusions that more correctly reflect the ignorance and uncertainties that result from partially uncertain input arguments.
The book will help researchers and practitioners to advance, improve and apply subjective logic to build powerful artificial reasoning models and tools for solving real-world problems. A good grounding in discrete mathematics is a prerequisite.
Описание: MBIA.- Non-rigid Registration of White Matter Tractography Using Coherent Point Drift Algorithm.- An Edge Enhanced SRGAN for MRI Super Resolution in Slice-selection Direction.- Exploring Functional Connectivity Biomarker in Autism Using Group-wise Sparse Representation.- Classifying Stages of Mild Cognitive Impairment via Augmented Graph Embedding.- Mapping the spatio-temporal functional coherence in the resting brain.- Species-Preserved Structural Connections Revealed by Sparse Tensor CCA.- Identification of Abnormal Cortical 3-hinge Folding Patterns on Autism Spectral Brains.- Exploring Brain Hemodynamic Response Patterns Via Deep Recurrent Autoencoder.- 3D Convolutional Long-short Term Memory Network for Spatiotemporal Modeling of fMRI Data.- Biological Knowledge Guided Deep Neural Network for Genotype-Phenotype Association Study.- Learning Human Cognition via fMRI Analysis Using 3D CNN and Graph Neural Network.- CU-Net: Cascaded U-Net with Loss Weighted Sampling for Brain Tumor Segmentation.- BrainPainter: A software for the visualisation of brain structures, biomarkers and associated pathological processes.- Structural Similarity based Anatomical and Functional Brain Imaging Fusion.- Multimodal Brain Tumor Segmentation Using Encoder-Decoder with Hierarchical Separable Convolution.- Prioritizing Amyloid Imaging Biomarkers in Alzheimer's Disease via Learning to Rank.- MFCA.- Diffeomorphic Metric Learning and Template Optimization for Registration-Based Predictive Models.- 3D mapping of serial histology sections with anomalies using a novel robust deformable registration algorithm.- Spatiotemporal Modeling for Image Time Series with Appearance Change: Application to Early Brain Development.- Surface Foliation Based Brain Morphometry Analysis.- Mixture Probabilistic Principal Geodesic Analysis.- A Geodesic Mixed Effects Model in Kendall's Shape Space.- An as-invariant-as-possible GL+(3)-based Statistical Shape Model.
Описание: This book gathers selected papers presented at the conference "Advances in 3D Image and Graphics Representation, Analysis, Computing and Information Technology," one of the first initiatives devoted to the problems of 3D imaging in all contemporary scientific and application areas.
Автор: Herrera Francisco, Ventura Sebastiбn, Bello Rafael Название: Multiple Instance Learning: Foundations and Algorithms ISBN: 3319838156 ISBN-13(EAN): 9783319838151 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a general overview of multiple instance learning (MIL), defining the framework and covering the central paradigms.
