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Titlebook: Computational Intelligence in Music, Sound, Art and Design; 8th International Co Anikó Ekárt,Antonios Liapis,María Luz Castro Pena Conferen

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書目名稱Computational Intelligence in Music, Sound, Art and Design
副標(biāo)題8th International Co
編輯Anikó Ekárt,Antonios Liapis,María Luz Castro Pena
視頻videohttp://file.papertrans.cn/233/232522/232522.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computational Intelligence in Music, Sound, Art and Design; 8th International Co Anikó Ekárt,Antonios Liapis,María Luz Castro Pena Conferen
描述.This book constitutes the refereed proceedings of the 8th International Conference on Evolutionary Computation in Combinatorial Optimization, EvoMUSART 2019, held in Leipzig, Germany, in April 2019, co-located with the Evo*2019 events EuroGP, EvoCOP and EvoApplications...The 16 revised full papers presented were carefully reviewed and selected from 24 submissions. The papers cover a wide range of topics and application areas, including: visual art and music generation, analysis, and interpretation; sound synthesis; architecture; video; poetry; design; and other creative tasks..
出版日期Conference proceedings 2019
關(guān)鍵詞artificial intelligence; data mining; evolutionary algorithms; evolutionary computation; fine arts; genet
版次1
doihttps://doi.org/10.1007/978-3-030-16667-0
isbn_softcover978-3-030-16666-3
isbn_ebook978-3-030-16667-0Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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978-3-030-16666-3Springer Nature Switzerland AG 2019
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/232522.jpg
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Strategies for Global and Regional Portsmmarise many decades of research and commentary around topics of autonomy, authenticity, authorship and intention in computer generated art, and use this research to answer contemporary questions often asked about art made by computers that concern these topics. We additionally reflect on whether cu
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https://doi.org/10.1007/978-1-349-22396-1on of shape informed by perception studies. Optimising swarms activity permits to efficiently identify shape-based keypoints to automatically annotate movement and is capable of producing meaningful qualitative descriptions for animation applications. When taken together as a set, these keypoints re
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https://doi.org/10.1007/978-1-349-22396-1 as possible, the locations of the vertices, the drawing order of the polygons and the RGBA color values must be optimized for the entire set at once. Because of the vast combinatorial space, the relatively simple constraints and the well-defined objective function, these optimization problems appea
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