no code implementations • 17 Jun 2020 • Nicolae-Cătălin Ristea, Radu Tudor Ionescu
Original and translated utterances are converted into spectrograms which are provided as input to a set of ResNet neural networks with various depths.
1 code implementation • 21 Jul 2020 • Nicolae-Cătălin Ristea, Andrei Anghel, Radu Tudor Ionescu
Moreover, considering the lack of databases for this task, we release as open source a large scale data set that closely replicates real world automotive scenarios for single-interference cases, allowing others to objectively compare their future work in this domain.
Signal Processing
1 code implementation • 11 Aug 2020 • Nicolae-Cătălin Ristea, Andrei Anghel, Radu Tudor Ionescu
In order to train our network in a real-world scenario, we introduce a new data set of realistic automotive radar signals with multiple targets and multiple interferers.
no code implementations • 14 Oct 2020 • Nicolae-Cătălin Ristea, Andrei Anghel, Radu Tudor Ionescu, Yonina C. Eldar
In autonomous driving, radar systems play an important role in detecting targets such as other vehicles on the road.
1 code implementation • 24 Aug 2022 • Evgenii Indenbom, Nicolae-Cătălin Ristea, Ando Saabas, Tanel Pärnamaa, Jegor Gužvin
Since acoustic echo is one of the major sources of poor audio quality, a wide variety of deep models have been proposed.
no code implementations • 29 Sep 2022 • Nicolae-Cătălin Ristea, Andrei Anghel, Mihai Datcu, Bertrand Chapron
Spaceborne synthetic aperture radar (SAR) can provide accurate images of the ocean surface roughness day-or-night in nearly all weather conditions, being an unique asset for many geophysical applications.
no code implementations • 12 Mar 2023 • Ross Cutler, Ando Saabas, Babak Naderi, Nicolae-Cătălin Ristea, Sebastian Braun, Solomiya Branets
The ICASSP 2023 Speech Signal Improvement Challenge is intended to stimulate research in the area of improving the speech signal quality in communication systems.