Name: Computational Texture and Patterns: From Textons to Deep Learning
Price: 58.21 EUR
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Author: Dana, Kristin J.
ISBN: 9783031006951

portada Computational Texture and Patterns: From Textons to Deep Learning

Computational Texture and Patterns: From Textons to Deep Learning

Type

Physical Book

Author

Kristin J. Dana

Publisher

Springer

Language

English

Pages

Format

Paperback

Dimensions

23.5 x 19.1 x 0.6 cm

Weight

0.21 kg.

ISBN13

9783031006951

Edition No.

Synopsis "Computational Texture and Patterns: From Textons to Deep Learning"

Visual pattern analysis is a fundamental tool in mining data for knowledge. Computational representations for patterns and texture allow us to summarize, store, compare, and label in order to learn about the physical world. Our ability to capture visual imagery with cameras and sensors has resulted in vast amounts of raw data, but using this information effectively in a task-specific manner requires sophisticated computational representations. We enumerate specific desirable traits for these representations: (1) intraclass invariance--to support recognition; (2) illumination and geometric invariance for robustness to imaging conditions; (3) support for prediction and synthesis to use the model to infer continuation of the pattern; (4) support for change detection to detect anomalies and perturbations; and (5) support for physics-based interpretation to infer system properties from appearance. In recent years, computer vision has undergone a metamorphosis with classic algorithms adaptingto new trends in deep learning. This text provides a tour of algorithm evolution including pattern recognition, segmentation and synthesis. We consider the general relevance and prominence of visual pattern analysis and applications that rely on computational models.

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Computational Texture and Patterns: From Textons to Deep Learning - Dana, Kristin J.

Synopsis "Computational Texture and Patterns: From Textons to Deep Learning"

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