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staff:vatolkin:publications [2022-08-13 18:11] igor.vatolkin [Peer-Reviewed Conference Proceedings] |
staff:vatolkin:publications [2022-10-29 09:13] igor.vatolkin [Peer-Reviewed Conference Proceedings] |
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| <html><b><font color=#006633>[c40]</font></b> <i> I. Vatolkin and C. McKay</i>:<b><font color=#0000FF> Stability of Symbolic Feature Group Importance in the Context of Multi-Modal Music Classification</font></b>. Accepted for Proceedings of the The 23rd International Society for Music Information Retrieval Conference (ISMIR), <font color=#996600>2022</font></html> | <html><b><font color=#006633>[c40]</font></b> <i> I. Vatolkin and C. McKay</i>:<b><font color=#0000FF> Stability of Symbolic Feature Group Importance in the Context of Multi-Modal Music Classification</font></b>. Accepted for Proceedings of the The 23rd International Society for Music Information Retrieval Conference (ISMIR), <font color=#996600>2022</font></html> | ||
| - | <html><b><font color=#006633>[c39]</font></b> <i> F. Ostermann, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Identification of the Most Relevant Zygonic Statistics and Semantic Audio Features for Genre Recognition</font></b>. Accepted for Proceedings of the 3rd Conference on AI Music Creativity (AIMC), <font color=#996600>2022</font></html> | + | <html><b><font color=#006633>[c39]</font></b> <i> F. Ostermann, I. Vatolkin, and G. Rudolph</i>:<b><font color=#0000FF> Artificial Music Producer: Filtering Music Compositions by Artificial Taste</font></b>. Accepted for Proceedings of the 3rd Conference on AI Music Creativity (AIMC), <font color=#996600>2022</font></html> |
| <html><b><font color=#006633>[c38]</font></b> <i> I. Vatolkin</i>:<b><font color=#0000FF> Identification of the Most Relevant Zygonic Statistics and Semantic Audio Features for Genre Recognition</font></b>. Accepted for Proceedings of the International Computer Music Conference (ICMC), <font color=#996600>2022</font></html> | <html><b><font color=#006633>[c38]</font></b> <i> I. Vatolkin</i>:<b><font color=#0000FF> Identification of the Most Relevant Zygonic Statistics and Semantic Audio Features for Genre Recognition</font></b>. Accepted for Proceedings of the International Computer Music Conference (ICMC), <font color=#996600>2022</font></html> | ||