Ghent University Academic Bibliography

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A new conformal map for polynomial chaos applied to direction-of-arrival estimation via UCA root-music

Seppe Van Brandt (UGent) , Jo Verhaevert (UGent) , Tanja Van Hecke (UGent) and Hendrik Rogier (UGent)

(2022) SENSORS. 22(14).
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Exploiting temporal context in CNN based multisource DOA estimation

Alexander Bohlender (UGent) , Ann Spriet, Wouter Tirry and Nilesh Madhu (UGent)

(2021) IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING. 29. p.1594-1608
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NMF-weighted SRP for multi-speaker direction of arrival estimation : robustness to spatial aliasing while exploiting sparsity in the atom-time domain

Sushmita Thakallapalli, Suryakanth V. Gangashetty and Nilesh Madhu (UGent)

(2021) EURASIP JOURNAL ON AUDIO SPEECH AND MUSIC PROCESSING. 2021.
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Neural networks using full-band and subband spatial features for mask based source separation

Alexander Bohlender (UGent) , Ann Spriet, Wouter Tirry and Nilesh Madhu (UGent)

(2021) 2021 29th European Signal Processing Conference (EUSIPCO). In European Signal Processing Conference p.346-350
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Least squares DOA estimation with an informed phase unwrapping and full bandwidth robustness

Alexander Bohlender (UGent) , A. Spriet, W. Tirry and Nilesh Madhu (UGent)

(2020) ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). In International Conference on Acoustics Speech and Signal Processing ICASSP p.4841-4845
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Efficient light collection and direction-of-arrival estimation using a photonic integrated circuit

Karel Van Acoleyen (UGent) , Eva Ryckeboer (UGent) , Wim Bogaerts (UGent) and Roel Baets (UGent)

(2012) IEEE PHOTONICS TECHNOLOGY LETTERS. 24(11). p.933-935

Academic Bibliography

A new conformal map for polynomial chaos applied to direction-of-arrival estimation via UCA root-music

Exploiting temporal context in CNN based multisource DOA estimation

NMF-weighted SRP for multi-speaker direction of arrival estimation : robustness to spatial aliasing while exploiting sparsity in the atom-time domain

Neural networks using full-band and subband spatial features for mask based source separation

Least squares DOA estimation with an informed phase unwrapping and full bandwidth robustness

Efficient light collection and direction-of-arrival estimation using a photonic integrated circuit

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