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staff:vatolkin:teachingtheses [2020-08-27 08:55]
Igor Vatolkin
staff:vatolkin:teachingtheses [2021-11-23 17:57]
Igor Vatolkin
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-===== Currently Supervised Theses (BT: Bachelor; MT: Master; DT: Diploma) =====+===== Currently Supervised Theses (BT: Bachelor; MT: Master) =====
  
-===== Past Theses =====+  * <​html><​b><​font color=#​006633>​[35] </​font><​font color=#​61380B>​MT </​font><​font color=#​0000FF>​Abstandsmaße zur evolutionären Klangapproximation auf Audiodaten (Distance measures for evolutionary approximation of audio data)</​font></​b></​html>​\\ // Philipp Ginsel; // 1. Reviewer: //G. Rudolph//; 2. Reviewer: //I. Vatolkin//​\\ <​html><​font color=#​996600>​2021</​font></​html>​  
 + 
 +  * <​html><​b><​font color=#​006633>​[34] </​font><​font color=#​61380B>​BT </​font><​font color=#​0000FF>​Optimierung der Berechnung von Zygonen im „Schuberts Winterreise Dataset“ mit beat-synchronen Audiomerkmalen ​ (Optimization of the calculation of zygones in "​Schuberts Winterreise Dataset"​ with beat-synchronized audio features)</​font></​b></​html>​\\ // Felix Wolff; // 1. Reviewer: //I. Vatolkin//; 2. Reviewer: //M. Ebeling//\\ <​html><​font color=#​996600>​2021</​font></​html>​  
 + 
 +  * <​html><​b><​font color=#​006633>​[33] </​font><​font color=#​61380B>​MT </​font><​font color=#​0000FF>​Einbeziehung verschiedener Klangkörper zum robusten Training neuronaler Netze für Instrumentenerkennung (Inclusion of different instrument bodies for robust training of neural networks for instrument recognition)</​font></​b></​html>​\\ // Florian Scholz; // 1. Reviewer: //I. Vatolkin//; 2. Reviewer: //H. Müller//\\ <​html><​font color=#​996600>​2021</​font></​html>​  
 + 
 +===== Past Theses ​(BT: Bachelor; MT: Master; DT: Diploma) ===== 
 + 
 +  * <​html><​b><​font color=#​006633>​[32] </​font><​font color=#​61380B>​BT </​font><​font color=#​0000FF>​Unterdrückung von Hintergrundgeräuschen in Sprachsignalen mit künstlichen neuronalen Netzen am Beispiel von Tastaturgeräuschen (Suppression of background noise in speech signals with artificial neural networks, exemplarily applied to keypad sound)</​font></​b></​html>​\\ // Leonard Fricke; // 1. Reviewer: //I. Vatolkin//; 2. Reviewer: //J. Kuzmic//\\ <​html><​font color=#​996600>​2021</​font></​html>​  
 + 
 +  * <​html><​b><​font color=#​006633>​[31] </​font><​font color=#​61380B>​BT </​font><​font color=#​0000FF>​Restaurierung von Klavierstücken mittels Convolutional Neural Networks, am Beispiel von Johannes Brahms' ​ Phonograph-Aufnahmen aus dem Jahre 1889 (Restoration of piano pieces of Johannes Brahms'​ phonograph recordings from 1889 with Convolutional Neural Networks)</​font></​b></​html>​\\ // Hassan Matout; // 1. Reviewer: //I. Vatolkin//; 2. Reviewer: //R. Kalkreuth//​\\ <​html><​font color=#​996600>​2021</​font></​html>​  
 + 
 +  * <​html><​b><​font color=#​006633>​[30] </​font><​font color=#​61380B>​BT </​font><​font color=#​0000FF>​Integration von Clusterverfahren in AMUSE (Integration of cluster methods in AMUSE)</​font></​b></​html>​\\ // Pauline Speckmann; // 1. Reviewer: //G. Rudolph//; 2. Reviewer: //I. Vatolkin//​\\ <​html><​font color=#​996600>​2021</​font></​html>​  
 + 
 +  * <​html><​b><​font color=#​006633>​[29] </​font><​font color=#​61380B>​MT </​font><​font color=#​0000FF>​Modellierung des menschlichen Musikgeschmacks mit neuronalen Netzen (Modelling of listener music preferences with neural networks)</​font></​b></​html>​\\ // Fabian Ostermann; // 1. Reviewer: //G. Rudolph//; 2. Reviewer: //I. Vatolkin//​\\ <​html><​font color=#​996600>​2021</​font></​html> ​
  
   * <​html><​b><​font color=#​006633>​[28] </​font><​font color=#​61380B>​MT </​font><​font color=#​0000FF>​Multimodale Klassifikation von Musik mit Bayesschen Netzen (Multi-modal classification of music with Bayes nets)</​font></​b></​html>​\\ // Tobias Klöppner; // 1. Reviewer: //G. Rudolph//; 2. Reviewer: //I. Vatolkin//​\\ <​html><​font color=#​996600>​2020</​font></​html> ​   * <​html><​b><​font color=#​006633>​[28] </​font><​font color=#​61380B>​MT </​font><​font color=#​0000FF>​Multimodale Klassifikation von Musik mit Bayesschen Netzen (Multi-modal classification of music with Bayes nets)</​font></​b></​html>​\\ // Tobias Klöppner; // 1. Reviewer: //G. Rudolph//; 2. Reviewer: //I. Vatolkin//​\\ <​html><​font color=#​996600>​2020</​font></​html> ​
  
-  * <​html><​b><​font color=#​006633>​[27] </​font><​font color=#​61380B>​MT </​font><​font color=#​0000FF>​Implementierung von hybriden Methoden zur Instrumentenerkennung in verrauschten Musikdaten (Implementation of hybrid methods for instrument recognition in augmented ​music data)</​font></​b></​html>​\\ // Benedikt Adrian; // 1. Reviewer: //I. Vatolkin//; 2. Reviewer: //J. Kuzmic//\\ <​html><​font color=#​996600>​2020</​font></​html> ​+  * <​html><​b><​font color=#​006633>​[27] </​font><​font color=#​61380B>​MT </​font><​font color=#​0000FF>​Implementierung von hybriden Methoden zur Instrumentenerkennung in verrauschten Musikdaten (Implementation of hybrid methods for instrument recognition in noisy music data)</​font></​b></​html>​\\ // Benedikt Adrian; // 1. Reviewer: //I. Vatolkin//; 2. Reviewer: //J. Kuzmic//\\ <​html><​font color=#​996600>​2020</​font></​html> ​
  
   * <​html><​b><​font color=#​006633>​[26] </​font><​font color=#​61380B>​BT </​font><​font color=#​0000FF>​Identifikation von effektiven Merkmalen für die Novelty-basierte Segmentierung (Identification of effective features for novelty based segemtation)</​font></​b></​html>​\\ // Marcel Rostowitz-Berkenkopf;​ // 1. Reviewer: //G. Rudolph//; 2. Reviewer: //I. Vatolkin//​\\ <​html><​font color=#​996600>​2020</​font></​html> ​   * <​html><​b><​font color=#​006633>​[26] </​font><​font color=#​61380B>​BT </​font><​font color=#​0000FF>​Identifikation von effektiven Merkmalen für die Novelty-basierte Segmentierung (Identification of effective features for novelty based segemtation)</​font></​b></​html>​\\ // Marcel Rostowitz-Berkenkopf;​ // 1. Reviewer: //G. Rudolph//; 2. Reviewer: //I. Vatolkin//​\\ <​html><​font color=#​996600>​2020</​font></​html> ​
 
Last modified: 2022-08-13 18:27 by Igor Vatolkin
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