Nebel, David

M.Sc.

Positionen

Mitarbeiter, Fachgruppe Mathematik, Fakultät Angewandte Computer- und Biowissenschaften

Forschungsschwerpunkt

Angewandte Informatik Forschungsschwerpunkt

ausgewählte Veröffentlichungen

Journalartikel
- Activation Functions for Generalized Learning Vector Quantization - A Performance Comparison. arXiv. 2019
- Data similarities, dissimilarities and types of inner products - a mathematical characterization in the context of machine learning. Machine Learning Reports. 18-28. 2015
- Median Variants of Learning Vector Quantization of Dissimilitary Data . Neurocomputing. 107-119. 2015
Sammelbandbeitrag
- Adaptive Hausdorff Distances and Tangent Distance Adaptation for Transformation Invariant Classification Learning. Neural Information Processing. 362-371. 2016
  
  PlumX Metrics
- Similarities, Dissimilarities and Types of Inner Products for Data Analysis in the Context of Machine Learning. Artificial Intelligence and Soft Computing 2016. 125-133. 2016
  
  PlumX Metrics
- Median-LVQ for Classification of Dissimilarity Data based on ROC-Optimization. Proceedings of the European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2015). 1-6. 2015
- Learning Vector Quantization with Adaptive Cost-Based Outlier-Rejection. Computer Analysis of Images and Patterns. 772-782. 2015
  
  PlumX Metrics

bearbeitet/e wissenschaftliche Arbeit

Promotion
- Promotion von David Nebel betreut von Villmann, Thomas

vollständiger Name

David Nebel

zugehörig zur Einrichtung

6-132

Postanschrift

Am Schwanenteich 4b

Mittweida

09648

Postadresse

Technikumplatz 17

Mittweida

09648

Deutschland

KoautorInnen-Netzwerk

Kontaktdaten

nebel@hs-mittweida.de

+49 3727 582293