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Produktnummer: 1870ef5dff9be34a11b88642dfbec2362a
Autor: Hung, Chih-Cheng Lan, Yihua Song, Enmin
Themengebiete: Convolutional Neural Networks (CNN) Deep Learning Digital Image Processing Image Texture Analysis K-View Model Texture Classification
Veröffentlichungsdatum: 06.10.2020
EAN: 9783030137755
Sprache: Englisch
Seitenzahl: 258
Produktart: Kartoniert / Broschiert
Verlag: Springer International Publishing
Untertitel: Foundations, Models and Algorithms
Produktinformationen "Image Texture Analysis"
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. Divided into three parts, the book opens with a review of existing models and algorithms for image texture analysis, before delving into the details of the K-views model. The work then concludes with a discussion of popular deep learning methods for image texture analysis.Topics and features: provides self-test exercises in every chapter; describes the basics of image texture, texture features, and image texture classification and segmentation; examines a selection of widely-used methods for measuring and extracting texture features, and various algorithms for texture classification; explains the concepts of dimensionality reduction and sparse representation; discusses view-based approaches to classifying images; introduces the template for the K-views algorithm, as well as a range of variants of this algorithm; reviews several neural network models for deep machine learning, and presents a specific focus on convolutional neural networks.This introductory text on image texture analysis is ideally suitable for senior undergraduate and first-year graduate students of computer science, who will benefit from the numerous clarifying examples provided throughout the work.

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