Have a personal or library account? Click to login

References

  1. [1] KIM, P. 2017. Matlab deep learning: With machine learning, Neural networks and Artificial Intelligence. Apress media, 2 p. ISBN-13: 978-1-4842-2844-9
  2. [2] HORSKÝ, D. 2018. Deep learning in musical instruments sound recognition. Diploma thesis.
  3. [3] KONCZ, I. 2019. Deep learning in music genre recognition. Diploma thesis.
  4. [4] MAJDAFA, V. 2018. Deep learning in music groups recognition. Diploma thesis.
  5. [5] DUGA, S. 2019. The use of deep learning in recognizing the voices of a group of people. Diploma thesis.
  6. [6] BACIGÁL, L. 2019. Deep learning in voice commands recognition. Diploma thesis.
  7. [7] TKÁČ, T. 2019. Deep learning in voice recognition for the operating system. Diploma thesis.
  8. [8] BENEDIKTOVIČ, M. 2018. Deep learning in paint styles recognition. Diploma thesis.
  9. [9] BENKA, D. 2019. Video post-processing by deep learning, 2019. Diploma thesis.
  10. [10] VAŽAN, P., JANÍKOVÁ, D., TANUŠKA, P., KEBÍSEK, M., ČERVEŇANSKÁ, Z. 2017. Using data mining methods for manufacturing process control. In: IFAC-PapersOnLine,50(1), pp. 6178-6183.10.1016/j.ifacol.2017.08.986
Language: English
Page range: 113 - 120
Submitted on: Aug 26, 2019
Accepted on: Oct 7, 2019
Published on: Dec 16, 2019
Published by: Slovak University of Technology in Bratislava
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2019 Marcel Nikmon, Roman Budjač, Daniel Kuchár, Peter Schreiber, Dagmar Janáčová, published by Slovak University of Technology in Bratislava
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.