Name: Image Texture Analysis: Foundations, Models and Algorithms (en Inglés)
SKU: 54781188
Price: 54.22 USD
Availability: InStock
Author: Hung, Chih-Cheng ; Song, Enmin ; Lan, Yihua
ISBN: 9783030137755

portada Image Texture Analysis: Foundations, Models and Algorithms (en Inglés)

Image Texture Analysis: Foundations, Models and Algorithms (en Inglés)

Formato

Libro Físico

Autor

Editorial

Idioma

Inglés

N° páginas

258

Encuadernación

Tapa Blanda

Dimensiones

23.4x15.6x1.4 cm

Peso

0.39 kg.

ISBN13

9783030137755

Categorías

Aplicaciones gráficas y multimedia
Inteligencia artificial

Image Texture Analysis: Foundations, Models and Algorithms (en Inglés)

Chih-Cheng Hung (Autor) · Enmin Song (Autor) · Yihua Lan (Autor) · Springer · Tapa Blanda

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Reseña del libro "Image Texture Analysis: Foundations, Models and Algorithms (en Inglés)"

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.