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staff:vatolkin:publications [2019-01-12 11:18]
staff:vatolkin:publications [2020-06-23 11:19]
igor.vatolkin [Peer-Reviewed Conference Proceedings]
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 ===== Book Chapters ===== ===== Book Chapters =====
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 +<​html><​b><​font color=#​006633>​[7]</​font></​b>​ <i>I. Vatolkin, A. Nagathil</​i>:<​b><​font color=#​0000FF>​ Evaluation of Audio Feature Groups for the Prediction of Arousal and Valence in Music</​font></​b>​. In: N. Bauer, K. Ickstadt, K. Lübke, G. Szepannek, H. Trautmann, M. Vichi (Eds.) (Eds.): Applications in Statistical Computing: From Music Data Analysis to Industrial Quality Improvement,​ Springer, <​html><​font color=#​996600>​2019</​font></​html>​
  
 <​html><​b><​font color=#​006633>​[6]</​font></​b>​ <i>I. Vatolkin, C. Weihs</​i>:<​b><​font color=#​0000FF>​ Evaluation</​font></​b>​. In: C. Weihs, D. Jannach, I. Vatolkin, G. Rudolph (Eds.): Music Data Analysis: Foundations and Applications,​ CRC Press, <​html><​font color=#​996600>​2016</​font></​html>​ <​html><​b><​font color=#​006633>​[6]</​font></​b>​ <i>I. Vatolkin, C. Weihs</​i>:<​b><​font color=#​0000FF>​ Evaluation</​font></​b>​. In: C. Weihs, D. Jannach, I. Vatolkin, G. Rudolph (Eds.): Music Data Analysis: Foundations and Applications,​ CRC Press, <​html><​font color=#​996600>​2016</​font></​html>​
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 ===== Peer-Reviewed Conference Proceedings ===== ===== Peer-Reviewed Conference Proceedings =====
  
-<​html><​b><​font color=#​006633>​[29]</​font></​b>​ <i> I. Vatolkin and D. Stoller</​i>:<​b><​font color=#​0000FF>​ Evolutionary Multi-Objective Training Set Selection of Data Instances and Augmentations for Vocal Detection</​font></​b>​. ​Accepted for Proceedings of the 8th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART),​ <font color=#​996600>​2019</​font></​html>​+<​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>​ 
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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>​. Accepted for Proceedings of the IEEE World Congress on Computational Intelligence (WCCI), <font color=#​996600>​2020</​font></​html>​ 
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 +<​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>​ 
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 +<​html><​b><​font color=#​006633>​[29]</​font></​b>​ <i> I. Vatolkin and D. Stoller</​i>:<​b><​font color=#​0000FF>​ Evolutionary Multi-Objective Training Set Selection of Data Instances and Augmentations for Vocal Detection</​font></​b>​. Proceedings of the 8th International Conference on Computational Intelligence in Music, Sound, Art and Design (EvoMUSART), pp. 201-216, <font color=#​996600>​2019</​font></​html>​
  
 <​html><​b><​font color=#​006633>​[28]</​font></​b>​ <i> I. Vatolkin and G. Rudolph</​i>:<​b><​font color=#​0000FF>​ Comparison of Audio Features for Recognition of Western and Ethnic ​ <​html><​b><​font color=#​006633>​[28]</​font></​b>​ <i> I. Vatolkin and G. Rudolph</​i>:<​b><​font color=#​0000FF>​ Comparison of Audio Features for Recognition of Western and Ethnic ​
 
Last modified: 2023-03-21 18:36 by igor.vatolkin
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