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Více informací o knize Image Texture Analysis

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• Anotace
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Anotace knihy

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.

Parametry knihy

Zařazení knihy Knihy v němčině Naturwissenschaften, Medizin, Informatik, Technik Informatik, EDV Anwendungs-Software

• Plný název: Image Texture Analysis
• Autor: Yihua Lan, Enmin Song
• Jazyk: Angličtina
• Vazba: Brožovaná
• Počet stran: 258
• EAN: 9783030137755
• ISBN: 3030137759
• ID: 33270939
• Nakladatelství: Springer Nature Switzerland AG
• Hmotnost: 454 g
• Rozměry: 235 × 155 × 15 mm
• Datum vydání: 06. October 2020

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