000 05569nam a22006495i 4500
001 978-3-030-72914-1
003 DE-He213
005 20240730175239.0
007 cr nn 008mamaa
008 210401s2021 sz | s |||| 0|eng d
020 _a9783030729141
_9978-3-030-72914-1
024 7 _a10.1007/978-3-030-72914-1
_2doi
050 4 _aQA75.5-76.95
072 7 _aUYA
_2bicssc
072 7 _aCOM014000
_2bisacsh
072 7 _aUYA
_2thema
082 0 4 _a004.0151
_223
245 1 0 _aArtificial Intelligence in Music, Sound, Art and Design
_h[electronic resource] :
_b10th International Conference, EvoMUSART 2021, Held as Part of EvoStar 2021, Virtual Event, April 7-9, 2021, Proceedings /
_cedited by Juan Romero, Tiago Martins, Nereida Rodríguez-Fernández.
250 _a1st ed. 2021.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2021.
300 _aXIII, 492 p. 236 illus., 181 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aTheoretical Computer Science and General Issues,
_x2512-2029 ;
_v12693
505 0 _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-InitiativeLevel 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 _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.
650 0 _aComputer science.
_99832
650 0 _aEducation
_xData processing.
_982607
650 0 _aMachine learning.
_91831
650 0 _aImage processing
_xDigital techniques.
_94145
650 0 _aComputer vision.
_9115985
650 0 _aArtificial intelligence.
_93407
650 0 _aSoftware engineering.
_94138
650 1 4 _aTheory of Computation.
_9115986
650 2 4 _aComputers and Education.
_941129
650 2 4 _aMachine Learning.
_91831
650 2 4 _aComputer Imaging, Vision, Pattern Recognition and Graphics.
_931569
650 2 4 _aArtificial Intelligence.
_93407
650 2 4 _aSoftware Engineering.
_94138
700 1 _aRomero, Juan.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9115987
700 1 _aMartins, Tiago.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9115988
700 1 _aRodríguez-Fernández, Nereida.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
_9115989
710 2 _aSpringerLink (Online service)
_9115990
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783030729134
776 0 8 _iPrinted edition:
_z9783030729158
830 0 _aTheoretical Computer Science and General Issues,
_x2512-2029 ;
_v12693
_9115991
856 4 0 _uhttps://doi.org/10.1007/978-3-030-72914-1
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
912 _aZDB-2-LNC
942 _cELN
999 _c89838
_d89838