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staff:vatolkin:publications [2020-08-27 08:50] igor.vatolkin |
staff:vatolkin:publications [2021-04-25 20:54] igor.vatolkin |
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| ===== Peer-Reviewed Conference Proceedings ===== | ===== Peer-Reviewed Conference Proceedings ===== | ||
| - | <html><b><font color=#006633>[32]</font></b> <i> I. Vatolkin</i>:<b><font color=#0000FF> Evolutionary Approximation of Instrumental Texture in Polyphonic Audio Recordings</font></b>. Accepted for Proceedings of the IEEE World Congress on Computational Intelligence (WCCI), <font color=#996600>2020</font></html> | + | <html><b><font color=#006633>[36]</font></b> <i> I. Vatolkin, P. Ginsel, and G. Rudolph</i>:<b><font color=#0000FF> Advancements in the Music Information Retrieval Framework AMUSE over the Last Decade. </font></b>. Accepted for Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), <font color=#996600>2021</font></html> |
| - | <html><b><font color=#006633>[31]</font></b> <i> P. Ginsel, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Analysis of Structural Complexity Features for Music Genre Recognition</font></b>. Accepted for Proceedings of the IEEE World Congress on Computational Intelligence (WCCI), <font color=#996600>2020</font></html> | + | <html><b><font color=#006633>[35]</font></b> <i> I. Vatolkin, F. Ostermann, and M. Müller</i>:<b><font color=#0000FF> An Evolutionary Multi-Objective Feature Selection Approach for Detecting Music Segment Boundaries of Specific Types</font></b>. Accepted for Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), <font color=#996600>2021</font></html> |
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| + | <html><b><font color=#006633>[34]</font></b> <i> I. Vatolkin, B. Adrian, and J. Kuzmic</i>:<b><font color=#0000FF> A Fusion of Deep and Shallow Learning to Predict Genres Based on Instrument and Timbre Features</font></b>. Accepted for Proceedings of the 10th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART), <font color=#996600>2021</font></html> | ||
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| + | <html><b><font color=#006633>[33]</font></b> <i> I. Vatolkin, M. Koch, and M. Müller</i>:<b><font color=#0000FF> A Multi-Objective Evolutionary Approach to Identify Relevant Audio Features for Music Segmentation</font></b>. Accepted for Proceedings of the 10th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART), <font color=#996600>2021</font></html> | ||
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| + | <html><b><font color=#006633>[32]</font></b> <i> I. Vatolkin</i>:<b><font color=#0000FF> Evolutionary Approximation of Instrumental Texture in Polyphonic Audio Recordings</font></b>. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pp. 1-8, <font color=#996600>2020</font></html> | ||
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| + | <html><b><font color=#006633>[31]</font></b> <i> P. Ginsel, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Analysis of Structural Complexity Features for Music Genre Recognition</font></b>. Proceedings of the IEEE Congress on Evolutionary Computation (CEC), pp. 1-8, <font color=#996600>2020</font></html> | ||
| <html><b><font color=#006633>[30]</font></b> <i> F. Heerde, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Comparing Fuzzy Rule Based Approaches for Music Genre Classification</font></b>. Proceedings of the 9th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART), pp. 35-48, <font color=#996600>2020</font></html> | <html><b><font color=#006633>[30]</font></b> <i> F. Heerde, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Comparing Fuzzy Rule Based Approaches for Music Genre Classification</font></b>. Proceedings of the 9th International Conference on Artificial Intelligence in Music, Sound, Art and Design (EvoMUSART), pp. 35-48, <font color=#996600>2020</font></html> | ||