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Books > Computing & IT > Applications of computing > Image processing
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Image Texture Analysis - Foundations, Models and Algorithms (Hardcover, 1st ed. 2019)
Loot Price: R2,011
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Image Texture Analysis - Foundations, Models and Algorithms (Hardcover, 1st ed. 2019)
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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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