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Artificial Intelligence in Music, Sound, Art and Design: 9th International Conference, EvoMUSART 2020, Held as Part of EvoStar 2020, Seville, Spain, April 1517, 2020, Proceedings 1st ed. 2020 [Mīkstie vāki]

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  • Formāts: Paperback / softback, 227 pages, height x width: 235x155 mm, weight: 454 g, 86 Illustrations, color; 28 Illustrations, black and white; XII, 227 p. 114 illus., 86 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 12103
  • Izdošanas datums: 10-Apr-2020
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030438589
  • ISBN-13: 9783030438586
  • Mīkstie vāki
  • Cena: 46,91 €*
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  • Formāts: Paperback / softback, 227 pages, height x width: 235x155 mm, weight: 454 g, 86 Illustrations, color; 28 Illustrations, black and white; XII, 227 p. 114 illus., 86 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 12103
  • Izdošanas datums: 10-Apr-2020
  • Izdevniecība: Springer Nature Switzerland AG
  • ISBN-10: 3030438589
  • ISBN-13: 9783030438586

This book constitutes the refereed proceedings of the 9th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2020, held as part of Evo*2020, in Seville, Spain, in April 2020, co-located with the Evo*2020 events EuroGP, EvoCOP and EvoApplications.
The 15 revised full papers presented were carefully reviewed and selected from 31 submissions. The papers cover a wide spectrum of topics and application areas, including generative approaches to music and visual art, deep learning, and architecture.

A deep learning neural network for classifying good and bad photos.- Adapting and Enhancing Evolutionary Art for Casual Creation.- Comparing Fuzzy Rule Based Approaches for Music Genre Classification.- Quantum Zentanglement: Combining Picbreeder and Wave Function Collapse to Create Zentangles.- Emerging Technology System Evolution.- Fusion of Hilbert-Huang Transform and Deep Convolutional Neural Network for Predominant Musical Instruments Recognition.- Genetic Reverb: Synthesizing Artificial Reverberant Fields Via Genetic Algorithms.- Portraits of No One: An Interactive Installation.- Understanding Aesthetic Evaluation with Deep Learning.- An Aesthetic-Based Fitness Measure and a Framework for Guidance of Evolutionary Design in Architecture.- Objective Evaluation of Tonal Fitness for Chord Progressions.- Coevolving Artistic Images Using OMNIREP.- Sound Cells in Genetic Improvisation: An Evolutionary Model for Improvised Music.- Controlling Self-Organization in Generative Creative Systems.- Emulation Games. See and Be Seen, a Subjective Approach to Analog Computational Neuroscience.