Автор: Ahearn Luke Название: 3D Game Textures ISBN: 1138920061 ISBN-13(EAN): 9781138920064 Издательство: Taylor&Francis Рейтинг: Цена: 7961.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Revised to take new technology into account, this new edition is an ideal hands-on resource for creating textures, shaders, and materials. It contains expanded coverage of shader nodes, and its companion website has been updated to include video tutorials as well as updated samples.
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: 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: 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.
Автор: Zhou, Kevin Название: Deep Learning for Medical Image Analysis ISBN: 0128104082 ISBN-13(EAN): 9780128104088 Издательство: Elsevier Science Рейтинг: Цена: 16505.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas.
Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis.
Автор: Agn?s Desolneux; Lionel Moisan; Jean-Michel Morel Название: From Gestalt Theory to Image Analysis ISBN: 1441924817 ISBN-13(EAN): 9781441924810 Издательство: Springer Рейтинг: Цена: 8384.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book introduces a new theory in Computer Vision yielding elementary techniques to analyze digital images. These techniques are a mathematical formalization of the Gestalt theory. The text includes numerous illustrations, and chapter-end exercises, to reinforce understanding.
Описание: Following the success of the first edition, recent developments in the field of morphological image analysis called for an extended second edition. The text has been fully revised with the goal of improving its clarity while introducing new concepts of interest to real image analysis applications. One chapter devoted to texture analysis has been added. Main extensions include: discussion about multichannel images and their morphological processing, ordering relations on image partitions, connected operators and levellings, homotopy for greytone images, translation-invariant implementations of erosions and dilations by line segments, reinforced emphasis on rank-based morphological operators, grey tone hit-or-miss, ordered independent homotopic thinnings and anchored skeletons, self-dual geodesic transformation and reconstruction, area based self-dual filters, anti-centre, watershed-based texture segmentation, texture models, and new scientific and industrial applications.
Автор: Nixon Название: Medical Image Understanding and Analysis ISBN: 3319959204 ISBN-13(EAN): 9783319959207 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The papers are organized in topical sections on liver analysis, medical image analysis, texture and image analysis, MRI: applications and techniques, segmentation in medical images, CT: learning and planning, ocular imaging analysis, applications of medical image analysis.
Автор: Virginio Cantoni; G. Musso Название: Image Analysis and Processing ISBN: 146129312X ISBN-13(EAN): 9781461293125 Издательство: Springer Рейтинг: Цена: 12157.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: For the third time the Italian Group on Pattern Recogni tion has organized an International Conference on Image Analysis and Processing (lAP) gathering together the most active groups working in this area in our country.
Описание: Comprising papers on diverse aspects of bio-inspired models, soft computing and hybrid intelligent systems, the articles in this book are divided into four main parts that cover important research areas such as fuzzy and bio-inspired problem-solving models.
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.
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