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Bernhard Lehner
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Journal Articles
- 2023
- [j4]Christoph Kralovec
, Bernhard Lehner
, Markus Kirchmayr, Martin Schagerl
:
Sandwich Face Layer Debonding Detection and Size Estimation by Machine-Learning-Based Evaluation of Electromechanical Impedance Measurements. Sensors 23(6): 2910 (2023) - 2022
- [j3]Péter Kovács, Bernhard Lehner, Gregor Thummerer, Günther Mayr, Peter Burgholzer, Mario Huemer:
Surfing Virtual Waves to Thermal Tomography: From model- to deep learning-based reconstructions. IEEE Signal Process. Mag. 39(1): 55-67 (2022) - 2019
- [j2]Eric J. Humphrey
, Sravana Reddy, Prem Seetharaman, Aparna Kumar, Rachel M. Bittner
, Andrew M. Demetriou
, Sankalp Gulati, Andreas Jansson, Tristan Jehan, Bernhard Lehner
, Anna M. Kruspe, Luwei Yang:
An Introduction to Signal Processing for Singing-Voice Analysis: High Notes in the Effort to Automate the Understanding of Vocals in Music. IEEE Signal Process. Mag. 36(1): 82-94 (2019) - 2018
- [j1]Bernhard Lehner
, Jan Schlüter, Gerhard Widmer
:
Online, Loudness-Invariant Vocal Detection in Mixed Music Signals. IEEE ACM Trans. Audio Speech Lang. Process. 26(8): 1369-1380 (2018)
Conference and Workshop Papers
- 2023
- [c13]Leena Warmedinger, Martin Huber, Mira Anand, Bernhard Lehner, Carolin Walper, Larissa Gorzawski, Michele Thieme, Birgit Wessel, Achim Roth:
The New Hydrographic Hydrosheds Database Derived from the Tandem-X Dem. IGARSS 2023: 1485-1488 - 2022
- [c12]Messay Tafesse Tamire, Venkata Pathuri Bhuvana, Bernhard Lehner, Stefan Schuster, Andreas Och, Muhammad Nadeem Akram:
Acoustic Temperature Tomography using a UNet based Deep Learning Approach. EUSIPCO 2022: 1561-1565 - 2020
- [c11]Péter Kovács
, Bernhard Lehner, Gregor Thummerer, Günther Mayr, Peter Burgholzer, Mario Huemer:
A Hybrid Approach for Thermographic Imaging With Deep Learning. ICASSP 2020: 4277-4281 - 2018
- [c10]Jan Schlüter, Bernhard Lehner:
Zero-Mean Convolutions for Level-Invariant Singing Voice Detection. ISMIR 2018: 321-326 - 2017
- [c9]Hamid Eghbal-zadeh, Bernhard Lehner, Matthias Dorfer, Gerhard Widmer
:
A hybrid approach with multi-channel i-vectors and convolutional neural networks for acoustic scene classification. EUSIPCO 2017: 2749-2753 - 2015
- [c8]Bernhard Lehner, Gerhard Widmer
, Sebastian Böck:
A low-latency, real-time-capable singing voice detection method with LSTM recurrent neural networks. EUSIPCO 2015: 21-25 - [c7]Bernhard Lehner, Gerhard Widmer, Reinhard Sonnleitner:
Improving voice activity detection in movies. INTERSPEECH 2015: 2942-2946 - [c6]Bernhard Lehner, Gerhard Widmer:
Monaural Blind Source Separation in the Context of Vocal Detection. ISMIR 2015: 309-315 - [c5]Hamid Eghbal-zadeh, Bernhard Lehner, Markus Schedl, Gerhard Widmer:
I-Vectors for Timbre-Based Music Similarity and Music Artist Classification. ISMIR 2015: 554-560 - [c4]Christian Dittmar, Bernhard Lehner, Thomas Prätzlich, Meinard Müller, Gerhard Widmer:
Cross-Version Singing Voice Detection in Classical Opera Recordings. ISMIR 2015: 618-624 - 2014
- [c3]Bernhard Lehner, Gerhard Widmer
, Reinhard Sonnleitner:
On the reduction of false positives in singing voice detection. ICASSP 2014: 7480-7484 - 2013
- [c2]Bernhard Lehner, Reinhard Sonnleitner, Gerhard Widmer:
Towards Light-Weight, Real-Time-Capable Singing Voice Detection. ISMIR 2013: 53-58 - 2009
- [c1]Lucia Terrenghi, Thomas Lang, Bernhard Lehner:
Elastic mobility: stretching interaction. Mobile HCI 2009
Informal and Other Publications
- 2024
- [i2]Claus Hofmann, Simon Schmid, Bernhard Lehner, Daniel Klotz, Sepp Hochreiter:
Energy-based Hopfield Boosting for Out-of-Distribution Detection. CoRR abs/2405.08766 (2024) - 2017
- [i1]Hamid Eghbal-zadeh, Bernhard Lehner, Matthias Dorfer, Gerhard Widmer:
A Hybrid Approach with Multi-channel I-Vectors and Convolutional Neural Networks for Acoustic Scene Classification. CoRR abs/1706.06525 (2017)
Coauthor Index
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