| Título : |
10th International Conference, EvoMUSART 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings |
| Tipo de documento: |
documento electrónico |
| Autores: |
Romero, Juan, ; Martins, Tiago, ; Rodríguez-Fernández, Nereida, |
| Mención de edición: |
1 ed. |
| Editorial: |
[s.l.] : Springer |
| Fecha de publicación: |
2021 |
| Número de páginas: |
XIII, 492 p. 236 ilustraciones, 181 ilustraciones en color. |
| ISBN/ISSN/DL: |
978-3-030-72914-1 |
| Nota general: |
Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos. |
| Palabras clave: |
Ciencias de la Computación Aprendizaje automático Procesamiento de imágenes Visión por computador Inteligencia artificial Ingeniería de software Teoría de la Computación Computadoras y Educación Imágenes por computadora visión reconocimiento de patrones y gráficos |
| Índice Dewey: |
40.151 |
| Resumen: |
Este libro constituye las actas arbitradas de la 10.ª Conferencia Europea sobre Inteligencia Artificial en Música, Sonido, Arte y Diseño, EvoMUSART 2021, celebrada como parte de Evo* 2021, como evento virtual, en abril de 2021, ubicado conjuntamente con Evo* 2021. eventos, EvoCOP, EvoApplications y EuroGP. Los 24 artículos completos revisados y los 7 artículos breves presentados en este libro fueron cuidadosamente revisados y seleccionados entre 66 presentaciones. Cubren una amplia gama de temas y áreas de aplicación, incluidos enfoques generativos de la música y las artes visuales, el aprendizaje profundo y la arquitectura. |
| Nota de contenido: |
Sculpture 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. |
| En línea: |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
| Link: |
https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i |
10th International Conference, EvoMUSART 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings [documento electrónico] / Romero, Juan, ; Martins, Tiago, ; Rodríguez-Fernández, Nereida, . - 1 ed. . - [s.l.] : Springer, 2021 . - XIII, 492 p. 236 ilustraciones, 181 ilustraciones en color. ISBN : 978-3-030-72914-1 Libro disponible en la plataforma SpringerLink. Descarga y lectura en formatos PDF, HTML y ePub. Descarga completa o por capítulos.
| Palabras clave: |
Ciencias de la Computación Aprendizaje automático Procesamiento de imágenes Visión por computador Inteligencia artificial Ingeniería de software Teoría de la Computación Computadoras y Educación Imágenes por computadora visión reconocimiento de patrones y gráficos |
| Índice Dewey: |
40.151 |
| Resumen: |
Este libro constituye las actas arbitradas de la 10.ª Conferencia Europea sobre Inteligencia Artificial en Música, Sonido, Arte y Diseño, EvoMUSART 2021, celebrada como parte de Evo* 2021, como evento virtual, en abril de 2021, ubicado conjuntamente con Evo* 2021. eventos, EvoCOP, EvoApplications y EuroGP. Los 24 artículos completos revisados y los 7 artículos breves presentados en este libro fueron cuidadosamente revisados y seleccionados entre 66 presentaciones. Cubren una amplia gama de temas y áreas de aplicación, incluidos enfoques generativos de la música y las artes visuales, el aprendizaje profundo y la arquitectura. |
| Nota de contenido: |
Sculpture 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. |
| En línea: |
https://link-springer-com.biblioproxy.umanizales.edu.co/referencework/10.1007/97 [...] |
| Link: |
https://biblioteca.umanizales.edu.co/ils/opac_css/index.php?lvl=notice_display&i |
|  |
Hacer una sugerencia Refinar búsqueda10th International Conference, EvoMUSART 2021, Held as Part of EvoStar 2021, Virtual Event, April 7–9, 2021, Proceedings / Romero, Juan ; Martins, Tiago ; Rodríguez-Fernández, Nereida
