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Can I read Computational Texture and Patterns: From Textons to Deep Learning (Synthesis Lectures on Computer Vision) on EtoBox?

Computational Texture and Patterns: From Textons to Deep Learning (Synthesis Lectures on Computer Vision) by Sven Dickinson (editor), Gerard Medioni (editor), Kristin J. Dana is a nonfiction available to read on EtoBox.

What is Computational Texture and Patterns: From Textons to Deep Learning (Synthesis Lectures on Computer Vision) about?

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 invarianceto 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 adapting to 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

Who reads Computational Texture and Patterns: From Textons to Deep Learning (Synthesis Lectures on Computer Vision)?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Sven Dickinson (editor), Gerard Medioni (editor), Kristin J. Dana
Publisher
Morgan & Claypool Publishers
Published
2018
Language
EN
ISBN
9783031006951
Category
nonfiction
Subjects
Engineering, Computer Science, Stem

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