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Computational Intelligence in Music, Sound, Art and Design

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Cover of 'Computational Intelligence in Music, Sound, Art and Design'

Table of Contents

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    Book Overview
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    Chapter 1 Deep Learning Concepts for Evolutionary Art
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    Chapter 2 Adversarial Evolution and Deep Learning – How Does an Artist Play with Our Visual System?
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    Chapter 3 Autonomy, Authenticity, Authorship and Intention in Computer Generated Art
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    Chapter 4 Camera Obscurer: Generative Art for Design Inspiration
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    Chapter 5 Swarm-Based Identification of Animation Key Points from 2D-medialness Maps
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    Chapter 6 Paintings, Polygons and Plant Propagation
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    Chapter 7 Evolutionary Games for Audiovisual Works: Exploring the Demographic Prisoner’s Dilemma
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    Chapter 8 Emojinating: Evolving Emoji Blends
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    Chapter 9 Automatically Generating Engaging Presentation Slide Decks
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    Chapter 10 Tired of Choosing? Just Add Structure and Virtual Reality
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    Chapter 11 EvoChef: Show Me What to Cook! Artificial Evolution of Culinary Arts
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    Chapter 12 Comparing Models for Harmony Prediction in an Interactive Audio Looper
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    Chapter 13 Stochastic Synthesizer Patch Exploration in Edisyn
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    Chapter 14 Evolutionary Multi-objective Training Set Selection of Data Instances and Augmentations for Vocal Detection
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    Chapter 15 Automatic Jazz Melody Composition Through a Learning-Based Genetic Algorithm
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    Chapter 16 Exploring Transfer Functions in Evolved CTRNNs for Music Generation
Attention for Chapter 3: Autonomy, Authenticity, Authorship and Intention in Computer Generated Art
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Chapter title
Autonomy, Authenticity, Authorship and Intention in Computer Generated Art
Chapter number 3
Book title
Computational Intelligence in Music, Sound, Art and Design
Published by
Springer, Cham, April 2019
DOI 10.1007/978-3-030-16667-0_3
Book ISBNs
978-3-03-016666-3, 978-3-03-016667-0
Authors

Jon McCormack, Toby Gifford, Patrick Hutchings, McCormack, Jon, Gifford, Toby, Hutchings, Patrick

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 78 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 12%
Researcher 6 8%
Lecturer 5 6%
Student > Bachelor 4 5%
Student > Master 4 5%
Other 9 12%
Unknown 41 53%
Readers by discipline Count As %
Computer Science 11 14%
Arts and Humanities 6 8%
Social Sciences 5 6%
Engineering 3 4%
Mathematics 2 3%
Other 6 8%
Unknown 45 58%