東華大學圖書館 |

Artificial intelligence in music, sound, art and design = 10th International Conference, EvoMUSART 2021, held as part of EvoStar 2021, Virtual Event, April 7-9, 2021 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Artificial intelligence in music, sound, art and design/ edited by Juan Romero, Tiago Martins, Nereida Rodriguez-Fernandez.
Reminder of title:	10th International Conference, EvoMUSART 2021, held as part of EvoStar 2021, Virtual Event, April 7-9, 2021 : proceedings /
remainder title:	EvoMUSART 2021
other author:	Romero, Juan.
corporate name:	EvoMUSART (Conference)
Published:	Cham :Springer International Publishing : : 2021.,
Description:	xiii, 492 p. :ill., digital ;24 cm.
[NT 15003449]:	Sculpture Inspired Musical Composition, One Possible Approach -- Network Bending: Expressive Manipulation of Deep Generative Models -- SyVMO: Synchronous Variable Markov Oracle for Modeling and Predicting Multi-Part Musical Structures -- Identification of Pure Painting Pigment Using Machine Learning Algorithms -- Evolving Neural Style Transfer Blends -- Evolving Image Enhancement Pipelines -- Genre Recognition from Symbolic Music with CNNs -- Axial Generation: A Concretism-Inspired Method for Synthesizing Highly Varied Artworks -- Interactive, Efficient and Creative Image Generation Using Compositional Pattern-Producing Networks -- Aesthetic Evaluation of Cellular Automata Configurations Using Spatial Complexity and Kolmogorov Complexity -- Auralization of Three-Dimensional Cellular Automata -- Chord Embeddings: Analyzing What They Capture and Their Role for Next Chord Prediction and Artist Attribute Prediction -- Convolutional Generative Adversarial Network, via Transfer Learning, for Traditional Scottish Music Generation -- The Enigma of Complexity -- SerumRNN: Step by Step Audio VST Effect Programming -- Parameter Tuning for Wavelet-Based Sound Event Detection Using Neural Networks -- Raga Recognition in Indian Classical Music Using Deep Learning -- The Simulated Emergence of Chord Function -- Incremental Evolution of Stylized Images -- Dissecting Neural Networks Filter Responses for Artistic Style Transfer -- A Fusion of Deep and Shallow Learning to Predict Genres Based on Instrument and Timbre Features -- A Multi-Objective Evolutionary Approach to Identify Relevant Audio Features for Music Segmentation -- Exploring the Effect of Sampling Strategy on Movement Generation with Generative Neural Networks -- "A Good Algorithm Does Not Steal - It Imitates": The Originality Report as a Means of Measuring when a Music Generation Algorithm Copies too Much -- From Music to Image - A Computational Creativity Approach -- "What is human?" A Turing Test for Artistic Creativity -- Mixed-Initiative Level Design with RL Brush -- Creating a Digital Mirror of Creative Practice -- An Application for Evolutionary Music Composition Using Autoencoders -- A Swarm Grammar-Based Approach to Virtual World Generation -- Co-Creative Drawing with One-Shot Generative Models.
Contained By:	Springer Nature eBook
Subject:	Evolutionary programming (Computer science) - Congresses. -
Online resource:	https://doi.org/10.1007/978-3-030-72914-1
ISBN:	9783030729141

Artificial intelligence in music, sound, art and design = 10th International Conference, EvoMUSART 2021, held as part of EvoStar 2021, Virtual Event, April 7-9, 2021 : proceedings /
Artificial intelligence in music, sound, art and design10th International Conference, EvoMUSART 2021, held as part of EvoStar 2021, Virtual Event, April 7-9, 2021 : proceedings /[electronic resource] :EvoMUSART 2021edited by Juan Romero, Tiago Martins, Nereida Rodriguez-Fernandez. - Cham :Springer International Publishing :2021. - xiii, 492 p. :ill., digital ;24 cm. - Lecture notes in computer science,126930302-9743 ;. - Lecture notes in computer science ;12693..

Sculpture Inspired Musical Composition, One Possible Approach -- Network Bending: Expressive Manipulation of Deep Generative Models -- SyVMO: Synchronous Variable Markov Oracle for Modeling and Predicting Multi-Part Musical Structures -- Identification of Pure Painting Pigment Using Machine Learning Algorithms -- Evolving Neural Style Transfer Blends -- Evolving Image Enhancement Pipelines -- Genre Recognition from Symbolic Music with CNNs -- Axial Generation: A Concretism-Inspired Method for Synthesizing Highly Varied Artworks -- Interactive, Efficient and Creative Image Generation Using Compositional Pattern-Producing Networks -- Aesthetic Evaluation of Cellular Automata Configurations Using Spatial Complexity and Kolmogorov Complexity -- Auralization of Three-Dimensional Cellular Automata -- Chord Embeddings: Analyzing What They Capture and Their Role for Next Chord Prediction and Artist Attribute Prediction -- Convolutional Generative Adversarial Network, via Transfer Learning, for Traditional Scottish Music Generation -- The Enigma of Complexity -- SerumRNN: Step by Step Audio VST Effect Programming -- Parameter Tuning for Wavelet-Based Sound Event Detection Using Neural Networks -- Raga Recognition in Indian Classical Music Using Deep Learning -- The Simulated Emergence of Chord Function -- Incremental Evolution of Stylized Images -- Dissecting Neural Networks Filter Responses for Artistic Style Transfer -- A Fusion of Deep and Shallow Learning to Predict Genres Based on Instrument and Timbre Features -- A Multi-Objective Evolutionary Approach to Identify Relevant Audio Features for Music Segmentation -- Exploring the Effect of Sampling Strategy on Movement Generation with Generative Neural Networks -- "A Good Algorithm Does Not Steal - It Imitates": The Originality Report as a Means of Measuring when a Music Generation Algorithm Copies too Much -- From Music to Image - A Computational Creativity Approach -- "What is human?" A Turing Test for Artistic Creativity -- Mixed-Initiative Level Design with RL Brush -- Creating a Digital Mirror of Creative Practice -- An Application for Evolutionary Music Composition Using Autoencoders -- A Swarm Grammar-Based Approach to Virtual World Generation -- Co-Creative Drawing with One-Shot Generative Models.

This book constitutes the refereed proceedings of the 10th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2021, held as part of Evo* 2021, as Virtual Event, in April 2021, co-located with the Evo* 2021 events, EvoCOP, EvoApplications, and EuroGP. The 24 revised full papers and 7 short papers presented in this book were carefully reviewed and selected from 66 submissions. They cover a wide range of topics and application areas, including generative approaches to music and visual art, deep learning, and architecture.

ISBN: 9783030729141

Standard No.: 10.1007/978-3-030-72914-1doiSubjects--Topical Terms:

582174
Evolutionary programming (Computer science)
--Congresses.

LC Class. No.: QA76.618 / .E86 2021

Dewey Class. No.: 005.11

Artificial intelligence in music, sound, art and design = 10th International Conference, EvoMUSART 2021, held as part of EvoStar 2021, Virtual Event, April 7-9, 2021 : proceedings /
LDR:04221nmm a2200385 a 4500 001 2238926
003 DE-He213
005 20210401050328.0
006 m d
007 cr nn 008maaau
008 211111s2021 sz s 0 eng d
020 $a 9783030729141 $q (electronic bk.)
020 $a 9783030729134 $q (paper)
024 7 $a 10.1007/978-3-030-72914-1 $2 doi
035 $a 978-3-030-72914-1
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.618 $b .E86 2021
072 7 $a UY $2 bicssc
072 7 $a COM014000 $2 bisacsh
072 7 $a UY $2 thema
072 7 $a UYA $2 thema
082 0 4 $a 005.11 $2 23
090 $a QA76.618 $b .E93 2021
111 2 $a EvoMUSART (Conference) $n (10th : $d 2021 : $c Online) $3 3492477
245 1 0 $a Artificial intelligence in music, sound, art and design $h [electronic resource] : $b 10th International Conference, EvoMUSART 2021, held as part of EvoStar 2021, Virtual Event, April 7-9, 2021 : proceedings / $c edited by Juan Romero, Tiago Martins, Nereida Rodriguez-Fernandez.
246 3 $a EvoMUSART 2021
246 3 $a EvoStar 2021
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2021.
300 $a xiii, 492 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 12693
490 1 $a Theoretical computer science and general issues
505 0 $a Sculpture Inspired Musical Composition, One Possible Approach -- Network Bending: Expressive Manipulation of Deep Generative Models -- SyVMO: Synchronous Variable Markov Oracle for Modeling and Predicting Multi-Part Musical Structures -- Identification of Pure Painting Pigment Using Machine Learning Algorithms -- Evolving Neural Style Transfer Blends -- Evolving Image Enhancement Pipelines -- Genre Recognition from Symbolic Music with CNNs -- Axial Generation: A Concretism-Inspired Method for Synthesizing Highly Varied Artworks -- Interactive, Efficient and Creative Image Generation Using Compositional Pattern-Producing Networks -- Aesthetic Evaluation of Cellular Automata Configurations Using Spatial Complexity and Kolmogorov Complexity -- Auralization of Three-Dimensional Cellular Automata -- Chord Embeddings: Analyzing What They Capture and Their Role for Next Chord Prediction and Artist Attribute Prediction -- Convolutional Generative Adversarial Network, via Transfer Learning, for Traditional Scottish Music Generation -- The Enigma of Complexity -- SerumRNN: Step by Step Audio VST Effect Programming -- Parameter Tuning for Wavelet-Based Sound Event Detection Using Neural Networks -- Raga Recognition in Indian Classical Music Using Deep Learning -- The Simulated Emergence of Chord Function -- Incremental Evolution of Stylized Images -- Dissecting Neural Networks Filter Responses for Artistic Style Transfer -- A Fusion of Deep and Shallow Learning to Predict Genres Based on Instrument and Timbre Features -- A Multi-Objective Evolutionary Approach to Identify Relevant Audio Features for Music Segmentation -- Exploring the Effect of Sampling Strategy on Movement Generation with Generative Neural Networks -- "A Good Algorithm Does Not Steal - It Imitates": The Originality Report as a Means of Measuring when a Music Generation Algorithm Copies too Much -- From Music to Image - A Computational Creativity Approach -- "What is human?" A Turing Test for Artistic Creativity -- Mixed-Initiative Level Design with RL Brush -- Creating a Digital Mirror of Creative Practice -- An Application for Evolutionary Music Composition Using Autoencoders -- A Swarm Grammar-Based Approach to Virtual World Generation -- Co-Creative Drawing with One-Shot Generative Models.
520 $a This book constitutes the refereed proceedings of the 10th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2021, held as part of Evo* 2021, as Virtual Event, in April 2021, co-located with the Evo* 2021 events, EvoCOP, EvoApplications, and EuroGP. The 24 revised full papers and 7 short papers presented in this book were carefully reviewed and selected from 66 submissions. They cover a wide range of topics and application areas, including generative approaches to music and visual art, deep learning, and architecture.
650 0 $a Evolutionary programming (Computer science) $x Congresses. $3 582174
650 0 $a Natural computation $v Congresses. $3 1085469
650 0 $a Computer music $x Congresses. $3 596474
650 0 $a Computer art $v Congresses. $3 3226642
650 1 4 $a Theory of Computation. $3 892514
650 2 4 $a Computers and Education. $3 892757
650 2 4 $a Machine Learning. $3 3382522
650 2 4 $a Computer Imaging, Vision, Pattern Recognition and Graphics. $3 890871
650 2 4 $a Artificial Intelligence. $3 769149
650 2 4 $a Software Engineering/Programming and Operating Systems. $3 891214
700 1 $a Romero, Juan. $3 898896
700 1 $a Martins, Tiago. $3 3492478
700 1 $a Rodriguez-Fernandez, Nereida. $3 3492479
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a Lecture notes in computer science ; $v 12693. $3 3492480
830 0 $a Theoretical computer science and general issues. $3 3382501
856 4 0 $u https://doi.org/10.1007/978-3-030-72914-1
950 $a Computer Science (SpringerNature-11645)