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170502 ||| eng |
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|a 9783319557502
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|a Correia, João
|e [editor]
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| 245 |
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|a Computational Intelligence in Music, Sound, Art and Design
|h Elektronische Ressource
|b 6th International Conference, EvoMUSART 2017, Amsterdam, The Netherlands, April 19–21, 2017, Proceedings
|c edited by João Correia, Vic Ciesielski, Antonios Liapis
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| 250 |
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|a 1st ed. 2017
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2017, 2017
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| 300 |
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|a X, 371 p. 169 illus
|b online resource
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|a Algorithmic Songwriting with ALYSIA -- On Symmetry, Aesthetics and Quantifying Symmetrical Complexity -- Towards Polyphony Reconstruction Using Multidimensional Multiple Sequence Alignment -- Melody Retrieval and Classification Using Biologically-Inspired Techniques -- Evolved Aesthetic Analogies to Improve Artistic Experience -- Deep Artificial Composer: A Creative Neural Network Model for Automated Melody Generation -- A Kind of Bio-inspired Learning of mUsic stylE -- Using Autonomous Agents to Improvise Music Compositions in Real-time -- Generating Polyphonic Music Using Tied Parallel Networks -- Mixed-initiative Creative Drawing with webIconoscope -- Clustering Agents for the Evolution of Autonomous Musical Fitness -- EvoFashion: Customising Fashion Through Evolution -- A Swarm Environment for Experimental Performance and Improvisation -- Niche Constructing Drawing Robots -- Automated Shape Design by Grammatical Evolution -- Evolutionary Image Transition Using Random Walks -- Evaluation Rules forEvolutionary Generation of Drum Patterns in Jazz Solos -- Assessing Augmented Creativity: Putting a Lovelace Machine for Interactive Title Generation through a Human Creativity Test -- Play It again: Evolved Audio Effects and Synthesizer Programming -- Fashion Design Aid System with Application of Interactive Genetic Algorithms -- Generalization Performance of Western Instrument Recognition Models in Polyphonic Mixtures with Ethnic Samples -- Exploring the Exactitudes Portrait Series with Restricted Boltzmann Machines -- Evolving Mondrian-Style Artworks -- Predicting Expressive Bow Controls for Violin and Viola.
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|a Mathematical statistics
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|a Computer science / Mathematics
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| 653 |
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|a Computer vision
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| 653 |
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|a Probability and Statistics in Computer Science
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| 653 |
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|a Digital humanities
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Algorithms
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| 653 |
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|a Computer Vision
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| 653 |
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|a Data mining
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Data Mining and Knowledge Discovery
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| 653 |
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|a Digital Humanities
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| 700 |
1 |
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|a Ciesielski, Vic
|e [editor]
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| 700 |
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|a Liapis, Antonios
|e [editor]
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| 041 |
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7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
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|a Theoretical Computer Science and General Issues
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| 028 |
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|a 10.1007/978-3-319-55750-2
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| 856 |
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|u https://doi.org/10.1007/978-3-319-55750-2?nosfx=y
|x Verlag
|3 Volltext
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|a 518.1
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|a This book constitutes the refereed proceedings of the 6th International Conference on Evolutionary Computation in Combinatorial Optimization, EvoMUSART 2017, held in Amsterdam, The Netherlands, in April 2017, co-located with the Evo*2017 events EuroGP, EvoCOP and EvoApplications. The 24 revised full papers presented were carefully reviewed and selected from 29 submissions. The papers cover a wide range of topics and application areas, including: generative approaches to music, graphics, game content, and narrative; music information retrieval; computational aesthetics; the mechanics of interactive evolutionary computation; computer-aided design; and the art theory of evolutionary computation.
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