05677nam 22007935 450 99646438680331620230329235539.03-030-72914-110.1007/978-3-030-72914-1(CKB)4100000011867180(MiAaPQ)EBC6532698(Au-PeEL)EBL6532698(OCoLC)1245663408(DE-He213)978-3-030-72914-1(PPN)255289375(EXLCZ)99410000001186718020210401d2021 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierArtificial Intelligence in Music, Sound, Art and Design[electronic resource] 10th International Conference, EvoMUSART 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings /edited by Juan Romero, Tiago Martins, Nereida Rodríguez-Fernández1st ed. 2021.Cham :Springer International Publishing :Imprint: Springer,2021.1 online resource (501 pages) illustrationsTheoretical Computer Science and General Issues,2512-2029 ;126933-030-72913-3 Includes bibliographical references and index.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.Theoretical Computer Science and General Issues,2512-2029 ;12693Computer scienceEducation—Data processingMachine learningImage processing—Digital techniquesComputer visionArtificial intelligenceSoftware engineeringTheory of ComputationComputers and EducationMachine LearningComputer Imaging, Vision, Pattern Recognition and GraphicsArtificial IntelligenceSoftware EngineeringComputer science.Education—Data processing.Machine learning.Image processing—Digital techniques.Computer vision.Artificial intelligence.Software engineering.Theory of Computation.Computers and Education.Machine Learning.Computer Imaging, Vision, Pattern Recognition and Graphics.Artificial Intelligence.Software Engineering.005.11Martins TiagoRodríguez-Fernández NereidaRomero JuanMiAaPQMiAaPQMiAaPQBOOK996464386803316Artificial Intelligence in Music, Sound, Art and Design2257587UNISA