Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Adnan Husakovic"'
Publikováno v:
Applied Sciences, Vol 13, Iss 3, p 1843 (2023)
This paper provides novel insights into the robustness of machine learning and signal-processing-based acoustic material classification for material transport in modern iron- and steelmaking. The proposed method is designed to deal with the specific
Externí odkaz:
https://doaj.org/article/69b3223fe7fb479b8cd1b8a5ad88632a
Autor:
Maria Anneliese Klaffenbock, Kurt Pichler, Adnan Husakovic, Veronika Putz, Anna Mayrhofer, Yvonne Kappacher-Winter, Christian Kastl
Publikováno v:
2021 55th Asilomar Conference on Signals, Systems, and Computers.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::63823dd22d36ea261ea94cfef791da7f
https://doi.org/10.1109/ieeeconf53345.2021.9723235
https://doi.org/10.1109/ieeeconf53345.2021.9723235
Publikováno v:
Computer Aided Systems Theory – EUROCAST 2019 ISBN: 9783030450953
EUROCAST (2)
EUROCAST (2)
Robust classification strongly depends on the combination of properly chosen features and the classification algorithm. This paper investigates an autoencoder for feature fusion together with recurrent neural networks such as the Long Short-Term Memo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f640611f6f2ec61ca8948e7e1159fedd
https://doi.org/10.1007/978-3-030-45096-0_6
https://doi.org/10.1007/978-3-030-45096-0_6
Publikováno v:
2018 14th Symposium on Neural Networks and Applications (NEUREL).
This paper discusses the performance of machine learning classification algorithms based on psychoacoustic features for the monitoring of a material transport process. Reliable and robust classification strongly depends on the proper choice of the fe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4d1ebecbe41879440179c1a3bebfb41e
https://doi.org/10.1109/neurel.2018.8587031
https://doi.org/10.1109/neurel.2018.8587031