19 citations · 20 across the 9 of their papers we have counts for
9 papers
Cascaded Cross-Modal Transformer for Audio-Textual Classification
Nicolae-Catalin Ristea, Andrei Anghel, Radu Tudor Ionescu
Speech classification tasks often require powerful language understanding models to grasp useful features, which becomes problematic when limited training data is available. To att…
Sea Ice Segmentation From SAR Data by Convolutional Transformer Networks
Nicolae-Catalin Ristea, Andrei Anghel, Mihai Datcu
Sea ice is a crucial component of the Earth's climate system and is highly sensitive to changes in temperature and atmospheric conditions. Accurate and timely measurement of sea ic…
Explainable, Physics Aware, Trustworthy AI Paradigm Shift for Synthetic Aperture Radar
Mihai Datcu, Zhongling Huang, Andrei Anghel +2
The recognition or understanding of the scenes observed with a SAR system requires a broader range of cues, beyond the spatial context. These encompass but are not limited to: imag…
Guided Unsupervised Learning by Subaperture Decomposition for Ocean SAR Image Retrieval
Nicolae-Cătălin Ristea, Andrei Anghel, Mihai Datcu +1
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 g…
Guided deep learning by subaperture decomposition: ocean patterns from SAR imagery
Nicolae-Catalin Ristea, Andrei Anghel, Mihai Datcu +1
Spaceborne synthetic aperture radar can provide meters scale images of the ocean surface roughness day or night in nearly all weather conditions. This makes it a unique asset for m…
Automotive Radar Interference Mitigation with Unfolded Robust PCA based on Residual Overcomplete Auto-Encoder Blocks
Nicolae-Cătălin Ristea, Andrei Anghel, Radu Tudor Ionescu +1
In autonomous driving, radar systems play an important role in detecting targets such as other vehicles on the road. Radars mounted on different cars can interfere with each other,…
Estimating the Magnitude and Phase of Automotive Radar Signals under Multiple Interference Sources with Fully Convolutional Networks
Nicolae-Cătălin Ristea, Andrei Anghel, Radu Tudor Ionescu
Radar sensors are gradually becoming a wide-spread equipment for road vehicles, playing a crucial role in autonomous driving and road safety. The broad adoption of radar sensors in…
Fully Convolutional Neural Networks for Automotive Radar Interference Mitigation
Nicolae-Cătălin Ristea, Andrei Anghel, Radu Tudor Ionescu
The interest of the automotive industry has progressively focused on subjects related to driver assistance systems as well as autonomous cars. Cars combine a variety of sensors to…
Pulse radar with FPGA range compression for real time displacement and vibration monitoring
Mihai Tudose, Andrei Anghel, Remus Cacoveanu +1
This paper aims at presenting the basic functionality of a radar platform for real-time monitoring of displacement and vibration. The real time capabilities make the radar platform…