Advances in Spatio-Temporal Segmentation of Visual Data, Mashtalir Vladimir, Ruban Igor, Levashenko Vitaly
Автор: Vladimir Mashtalir; Igor Ruban; Vitaly Levashenko Название: Advances in Spatio-Temporal Segmentation of Visual Data ISBN: 3030354792 ISBN-13(EAN): 9783030354794 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book proposes a number of promising models and methods for adaptive segmentation, swarm partition, permissible segmentation, and transform properties, as well as techniques for spatio-temporal video segmentation and interpretation, online fuzzy clustering of data streams, and fuzzy systems for information retrieval.
Автор: Meyer, Fernand Название: Topographical tools for filtering and segmentation 1 ISBN: 1786301571 ISBN-13(EAN): 9781786301574 Издательство: Wiley Рейтинг: Цена: 146730.00 T Наличие на складе: Поставка под заказ. Описание:
Mathematical morphology has developed a powerful methodology for segmenting images, based on connected filters and watersheds. We have chosen the abstract framework of node- or edge-weighted graphs for an extensive mathematical and algorithmic description of these tools.
Volume 1 is devoted to watersheds. The topography of a graph appears by observing the evolution of a drop of water moving from node to node on a weighted graph, along flowing paths, until it reaches regional minima. The upstream nodes of a regional minimum constitute its catchment zone.
The catchment zones may be constructed independently of each other and locally, in contrast with the traditional approach where the catchment basins have to be constructed all at the same time. Catchment zones may overlap, and thus, a new segmentation paradigm is proposed in which catchment zones cover each other according to a priority order. The resulting partition may then be corrected, by local and parallel treatments, in order to achieve the desired precision.
Автор: Ayman El-Baz, Jasjit S. Suri Название: Level Set Method in Medical Imaging Segmentation ISBN: 113855345X ISBN-13(EAN): 9781138553453 Издательство: Taylor&Francis Рейтинг: Цена: 224570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Level set methods are numerical techniques which offer remarkably powerful tools for understanding, analyzing, and computing interface motion in a host of settings. When used for medical imaging analysis and segmentation, the function assigns a label to each pixel or voxel and optimality is defined based on desired imaging properties. This often includes a detection step to extract specific objects via segmentation. This allows for the segmentation and analysis problem to be formulated and solved in a principled way based on well-established mathematical theories. Level set method is a great tool for modeling time varying medical images and enhancement of numerical computations.
Автор: Meyer, Fernand Название: Topographical Tools for Filtering and Segmentation 2 ISBN: 1786304074 ISBN-13(EAN): 9781786304070 Издательство: Wiley Рейтинг: Цена: 146730.00 T Наличие на складе: Поставка под заказ. Описание:
Mathematical morphology has developed a powerful methodology for segmenting images, based on connected filters and watersheds. We have chosen the abstract framework of node- or edge-weighted graphs for an extensive mathematical and algorithmic description of these tools.
Volume 2 proposes two physical models for describing valid flooding on a node- or edge-weighted graph, and establishes how to pass from one to another. Many new flooding algorithms are derived, allowing parallel and local flooding of graphs.
Watersheds and flooding are then combined for solving real problems. Their ability to model a real hydrographic basin represented by its digital elevation model constitutes a good validity check of the underlying physical models.
The last part of Volume 2 explains why so many different watershed partitions exist for the same graph. Marker-based segmentation is the method of choice for curbing this proliferation. This book proposes new algorithms combining the advantages of the previous methods which treated node- and edge-weighted graphs differently.
Автор: Liew Alan Wee-Chung, Wang Shilin Название: Visual Speech Recognition: Lip Segmentation and Mapping ISBN: 1605661864 ISBN-13(EAN): 9781605661865 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 220710.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Presents an account of research done in the areas of lip segmentation, visual speech recognition, and speaker identification and verification. This book discusses topics such as visual speaker authentication, lip modeling, and systematic evaluation of lip features.
Автор: S. Dash, B.K. Tripathy Название: Data Clustering and Image Segmentation Through Genetic Algorithms: Emerging Research and Opportunities ISBN: 1522563199 ISBN-13(EAN): 9781522563198 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 189420.00 T Наличие на складе: Невозможна поставка. Описание: As computers are being used more and more to solve complex problems, the application of biology or natural evolution principles to the study and design of human systems helps provide efficient optimization algorithms.
Data Clustering and Image Segmentation Through Genetic Algorithms: Emerging Research and Opportunities is an essential reference source that discusses applications of bio-inspired algorithms in data mining, computer vision, image processing, and pattern recognition, as well as methods of designing competent algorithms based on decomposition principles. Featuring research on topics such as cluster analysis, metaheuristic optimization, and image processing, this book is ideally designed for IT professionals, computer engineers, researchers, academicians, and upper-level students seeking coverage on how to develop efficient clustering algorithms.
Автор: de Sourav, Bhattacharyya Siddhartha, Chakraborty Susanta Название: Hybrid Soft Computing for Multilevel Image and Data Segmentation ISBN: 3319837583 ISBN-13(EAN): 9783319837581 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Alireza Bab-Hadiashar; David Suter Название: Data Segmentation and Model Selection for Computer Vision ISBN: 1468495089 ISBN-13(EAN): 9781468495089 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This edited volume explores several issues relating to parametric segmentation including robust operations, model selection criteria and automatic model selection, plus 2D and 3D scene segmentation.
Автор: Sourav De; Siddhartha Bhattacharyya; Susanta Chakr Название: Hybrid Soft Computing for Multilevel Image and Data Segmentation ISBN: 3319475231 ISBN-13(EAN): 9783319475233 Издательство: Springer Рейтинг: Цена: 88500.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book explains efficient solutions for segmenting the intensity levels of different types of multilevel images. The authors present hybrid soft computing techniques, which have advantages over conventional soft computing solutions as they incorporate data heterogeneity into the clustering/segmentation procedures.This is a useful introduction and reference for researchers and graduate students of computer science and electronics engineering, particularly in the domains of image processing and computational intelligence.
Автор: Shusharina Nadya, Heinrich Mattias P., Huang Ruobing Название: Segmentation, Classification, and Registration of Multi-Modality Medical Imaging Data: Miccai 2020 Challenges, ABCs 2020, L2r 2020, Tn-Scui 2020, Held ISBN: 3030718263 ISBN-13(EAN): 9783030718268 Издательство: Springer Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. 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.
Автор: Meera Ramadas; Ajith Abraham Название: Metaheuristics for Data Clustering and Image Segmentation ISBN: 3030040968 ISBN-13(EAN): 9783030040963 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In this book, differential evolution and its modified variants are applied to the clustering of data and images. Metaheuristics have emerged as potential algorithms for dealing with complex optimization problems, which are otherwise difficult to solve using traditional methods. In this regard, differential evolution is considered to be a highly promising technique for optimization and is being used to solve various real-time problems. The book studies the algorithms in detail, tests them on a range of test images, and carefully analyzes their performance. Accordingly, it offers a valuable reference guide for all researchers, students and practitioners working in the fields of artificial intelligence, optimization and data analytics.
Автор: Branka Stojanovi?; Oge Marques; Aleksandar Ne?kovi Название: Segmentation and Separation of Overlapped Latent Fingerprints ISBN: 3030233634 ISBN-13(EAN): 9783030233631 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This Springerbrief presents an overview of problems and technologies behind segmentation and separation of overlapped latent fingerprints, which are two fundamental steps in the context of fingerprint matching systems. It addresses five main aspects: (1) the need for overlapped latent fingerprint segmentation and separation in the context of fingerprint verification systems; (2) the different datasets available for research on overlapped latent fingerprints; (3) selected algorithms and techniques for segmentation of overlapped latent fingerprints; (4) selected algorithms and techniques for separation of overlapped latent fingerprints; and (5) the use of deep learning techniques for segmentation and separation of overlapped latent fingerprints.
By offering a structured overview of the most important approaches currently available, putting them in perspective, and suggesting numerous resources for further exploration, this book gives its readers a clear path for learning new topics and engaging in related research. Written from a technical perspective, and yet using language and terminology accessible to non-experts, it describes the technologies, introduces relevant datasets, highlights the most important research results in each area, and outlines the most challenging open research questions.
This Springerbrief targets researchers, professionals and advanced-level students studying and working in computer science, who are interested in the field of fingerprint matching and biometrics. Readers who want to deepen their understanding of specific topics will find more than one hundred references to additional sources of related information.
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