Research output per year
Research output per year
- 14 results
Search results
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2023
Hopfield Boosting for Out-of-Distribution Detection
Hofmann, C., Schmid, S. L., Lehner, B., Klotz, D. & Hochreiter, S., 15 Dec 2023, (Accepted/In press) NeurIPS 2023 Workshop: Associative Memory & Hopfield Networks.Research output: Conference proceeding/Chapter in Book/Report/ › Conference Paper › peer-review
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Sandwich Face Layer Debonding Detection and Size Estimation by Machine-Learning-Based Evaluation of Electromechanical Impedance Measurements
Kralovec, C., Lehner, B., Kirchmayr, M. & Schagerl, M., 7 Mar 2023, In: Sensors.Research output: Contribution to journal › Article › peer-review
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2022
Surfing Virtual Waves to Thermal Tomography: From model- to deep learning-based reconstructions
Kovács, P., Lehner, B., Thummerer, G., Mayr, G., Burgholzer, P. & Huemer, M., Jan 2022, In: IEEE Signal Processing Magazine. 39, 1, p. 55-67Research output: Contribution to journal › Article › peer-review
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2021
A Deep Learning Approach for Network Anomaly Detection
Lehner, B., 2021Research output: Other contribution
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Uncertainty Estimation for Deep Learning-based Thermographic Imaging
Lehner, B., Gallien, T., Kovács, P., Thummerer, G., Mayr, G., Burgholzer, P. & Huemer, M., Feb 2021, In: Sensors and Transducers Journal. 249, 2, p. 25-35Research output: Contribution to journal › Article › peer-review
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2020
A Hybrid Approach for Thermographic Imaging With Deep Learning
Kovács, P., Lehner, B., Thummerer, G., Mayr, G., Burgholzer, P. & Huemer, M., 8 May 2020, ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). p. 4277-4281 5 p. 9053411Research output: Conference proceeding/Chapter in Book/Report/ › Conference Paper › peer-review
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Deep learning approaches for thermographic imaging
Kovács, P., Lehner, B., Thummerer, G., Mayr, G., Burgholzer, P. & Huemer, M., 21 Oct 2020, In: Journal of Applied Physics. 128, 15, p. 155103Research output: Contribution to journal › Article › peer-review
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Uncertainty estimation for non-destructive detection of material defects with u-nets
Lehner, B. & Gallien, T., 2020.Research output: Contribution to conference (No Proceedings) › Paper › peer-review
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2019
Acoustic Scene Classification with Reject Option Based on Resnets
Lehner, B., Koutini, K., Schwarzlmüller, C. H., Gallien, T. & Widmer, G., 1 Jun 2019.Research output: Working paper
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2018
Online, Loudness-Invariant Vocal Detection in Mixed Music Signals
Lehner, B., Schlüter, J. & Widmer, G., 1 Aug 2018, In: IEEE/ACM Transactions on Audio, Speech, and Language Processing. 26, 8, p. 1369-1380 12 p., 8334252.Research output: Contribution to journal › Article › peer-review
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Zero-mean convolutions for level-invariant singing voice detection
Schlüter, J. & Lehner, B., 2018, Proceedings of the 19th International Society for Music Information Retrieval Conference, ISMIR 2018. p. 321-326 6 p. (Proceedings of the 19th International Society for Music Information Retrieval Conference, ISMIR 2018).Research output: Conference proceeding/Chapter in Book/Report/ › Chapter › peer-review
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2017
A hybrid approach with multi-channel i-vectors and convolutional neural networks for acoustic scene classification
Eghbal-zadeh, H., Lehner, B., Dorfer, M. & Widmer, G., 2 Sept 2017, 2017 25th European Signal Processing Conference (EUSIPCO). p. 2749-2753 5 p. 8081711Research output: Conference proceeding/Chapter in Book/Report/ › Conference Paper › peer-review
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2015
A low-latency, real-time-capable singing voice detection method with LSTM recurrent neural networks
Lehner, B., Widmer, G. & Bock, S., 22 Dec 2015, 2015 23rd European Signal Processing Conference, EUSIPCO 2015. Institute of Electrical and Electronics Engineers Inc., p. 21-25 5 p. (2015 23rd European Signal Processing Conference, EUSIPCO 2015).Research output: Conference proceeding/Chapter in Book/Report/ › Chapter › peer-review
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Improving voice activity detection in movies
Lehner, B., Widmer, G. & Sonnleitner, R., 2015. 5 p.Research output: Contribution to conference (No Proceedings) › Paper › peer-review