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Titlebook: Evolutionary and Biologically Inspired Music, Sound, Art and Design; 4th International Co Colin Johnson,Adrian Carballal,Jo?o Correia Confe

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書目名稱Evolutionary and Biologically Inspired Music, Sound, Art and Design
副標(biāo)題4th International Co
編輯Colin Johnson,Adrian Carballal,Jo?o Correia
視頻videohttp://file.papertrans.cn/319/318047/318047.mp4
概述Includes supplementary material:
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Evolutionary and Biologically Inspired Music, Sound, Art and Design; 4th International Co Colin Johnson,Adrian Carballal,Jo?o Correia Confe
描述This book constitutes the refereed proceedings of the 4th International Conference on Biologically Inspired Music, Sound, Art and Design, EvoMUSART 2015, held in Copenhagen, Denmark, in April 2015, co-located with the Evo* 2015 events EuroGP, EvoCOP and Evo Applications. The 23 revised full papers presented were carefully reviewed and selected from 43 submissions. They 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 and the art theory of evolutionary computation.
出版日期Conference proceedings 2015
關(guān)鍵詞Algorithms; Ant Colony Optimization; Bioinformatics; Bionic Engineering; Computer Games; Distributed Syst
版次1
doihttps://doi.org/10.1007/978-3-319-16498-4
isbn_softcover978-3-319-16497-7
isbn_ebook978-3-319-16498-4Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2015
The information of publication is updating

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Feature Discovery by Deep Learning for Aesthetic Analysis of Evolved Abstract Images,ved abstract art images. Two Restricted Boltzmann Machine models were trained independently on low and high aesthetic class images. The receptive fields (filters) of both models were compared by visual inspection. Roughly 10?% of these filters in the high aesthetic model approximated the form of the
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A Genetic Programming Approach to Generating Musical Compositions,d music composition is proposed. It is inspired by genetic programming and uses a tree-based domain model of compositions. The model represents musical pieces as a set of constraints changing over time, forming musical contexts allowing to compose, reuse and reshape musical fragments. The system imp
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Toward Certain Sonic Properties of an Audio Feedback System by Evolutionary Control of Second-Ordering toward chosen sonic features. Users control the system by selecting and changing feature objectives in real-time. The system has a second-order structure in which the internal signal processing algorithms are developed according to an evolutionary process. Genotypes develop into signal-processin
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