001435594 000__ 05673cam\a2200685\a\4500 001435594 001__ 1435594 001435594 003__ OCoLC 001435594 005__ 20230309003902.0 001435594 006__ m\\\\\o\\d\\\\\\\\ 001435594 007__ cr\un\nnnunnun 001435594 008__ 210410s2021\\\\sz\\\\\\o\\\\\101\0\eng\d 001435594 019__ $$a1244805433 001435594 020__ $$a9783030729141$$q(electronic bk.) 001435594 020__ $$a3030729141$$q(electronic bk.) 001435594 020__ $$z9783030729134 001435594 020__ $$z3030729133 001435594 0247_ $$a10.1007/978-3-030-72914-1$$2doi 001435594 035__ $$aSP(OCoLC)1245663408 001435594 040__ $$aEBLCP$$beng$$epn$$cEBLCP$$dGW5XE$$dYDX$$dOCLCO$$dEBLCP$$dN$T$$dOCLCF$$dOCLCO$$dOCLCQ$$dCOM$$dOCLCO$$dOCLCQ 001435594 049__ $$aISEA 001435594 050_4 $$aQA76.618 001435594 08204 $$a005.1/1$$223 001435594 1112_ $$aEvoMUSART (Conference)$$n(10th :$$d2021 :$$cOnline) 001435594 24510 $$aArtificial intelligence in music, sound, art and design:$$b10th International Conference, EvoMUSART 2021, held as part of EvoStar 2021, Virtual Event, April 7-9, 2021, Proceedings /$$cJuan Romero, Tiago Martins, Nereida Rodríguez-Fernández (eds.). 001435594 2463_ $$aEvoMUSART 2021 001435594 260__ $$aCham :$$bSpringer,$$c2021. 001435594 300__ $$a1 online resource (501 pages) 001435594 336__ $$atext$$btxt$$2rdacontent 001435594 337__ $$acomputer$$bc$$2rdamedia 001435594 338__ $$aonline resource$$bcr$$2rdacarrier 001435594 4901_ $$aLecture Notes in Computer Science ;$$v12693 001435594 4901_ $$aLNCS sublibrary, SL 1, Theoretical computer science and general issues 001435594 500__ $$aIncludes author index. 001435594 5050_ $$aSculpture 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. 001435594 506__ $$aAccess limited to authorized users. 001435594 520__ $$aThis book constitutes the refereed proceedings of the 10th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2021, held as part of Evo* 2021, as Virtual Event, in April 2021, co-located with the Evo* 2021 events, EvoCOP, EvoApplications, and EuroGP. The 24 revised full papers and 7 short papers presented in this book were carefully reviewed and selected from 66 submissions. They cover a wide range of topics and application areas, including generative approaches to music and visual art, deep learning, and architecture. 001435594 588__ $$aDescription based on print version record. 001435594 650_0 $$aEvolutionary programming (Computer science)$$vCongresses. 001435594 650_0 $$aNatural computation$$vCongresses. 001435594 650_0 $$aComputer music$$vCongresses. 001435594 650_0 $$aComputer art$$vCongresses. 001435594 650_6 $$aProgrammation évolutive$$vCongrès. 001435594 650_6 $$aCalcul naturel$$vCongrès. 001435594 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772 001435594 655_7 $$aConference papers and proceedings.$$2lcgft 001435594 655_7 $$aActes de congrès.$$2rvmgf 001435594 655_0 $$aElectronic books. 001435594 7001_ $$aRomero, Juan. 001435594 7001_ $$aMartins, Tiago. 001435594 7001_ $$aRodríguez-Fernández, Nereida. 001435594 7112_ $$aEVOSTAR (Conference)$$d(2021 :$$cOnline) 001435594 77608 $$iPrint version:$$aRomero, Juan.$$tArtificial Intelligence in Music, Sound, Art and Design.$$dCham : Springer International Publishing AG, ©2021$$z9783030729134 001435594 830_0 $$aLecture notes in computer science ;$$v12693. 001435594 830_0 $$aLNCS sublibrary.$$nSL 1,$$pTheoretical computer science and general issues. 001435594 852__ $$bebk 001435594 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-72914-1$$zOnline Access$$91397441.1 001435594 909CO $$ooai:library.usi.edu:1435594$$pGLOBAL_SET 001435594 980__ $$aBIB 001435594 980__ $$aEBOOK 001435594 982__ $$aEbook 001435594 983__ $$aOnline 001435594 994__ $$a92$$bISE