Guided Unsupervised Learning by Subaperture Decomposition for Ocean SAR Image Retrieval

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. Considering the huge amount of data daily acquired by satellites, automated techniques for physical features extraction are needed. Even if supervised deep learning methods attain state-of-the-art results, they require great amount of labeled data, which are difficult and excessively expensive to acquire for ocean SAR imagery. To this end, we use the subaperture decomposition (SD) algorithm to enhance the unsupervised learning retrieval on the ocean surface, empowering ocean researchers to search into large ocean databases. We empirically prove that SD improve the retrieval precision with over 20% for an unsupervised transformer auto-encoder network. Moreover, we show that SD brings important performance boost when Doppler centroid images are used as input data, leading the way to new unsupervised physics guided retrieval algorithms

Deep model with built-in cross-attention alignment for acoustic echo cancellation

With recent research advances, deep learning models have become an attractive choice for acoustic echo cancellation (AEC) in real-time teleconferencing applications. Since acoustic echo is one of the major sources of poor audio quality, a wide variety of deep models have been proposed. However, an important but often omitted requirement for good echo cancellation quality is the synchronization of the microphone and far end signals. Typically implemented using classical algorithms based on cross-correlation, the alignment module is a separate functional block with known design limitations. In our work we propose a deep learning architecture with built-in self-attention based alignment, which is able to handle unaligned inputs, improving echo cancellation performance while simplifying the communication pipeline. Moreover, we show that our approach achieves significant improvements for difficult delay estimation cases on real recordings from AEC Challenge data set

ICASSP 2023 Speech Signal Improvement Challenge

The ICASSP 2023 Speech Signal Improvement Challenge is intended to stimulate research in the area of improving the speech signal quality in communication systems. The speech signal quality can be measured with SIG in ITU-T P.835 and is still a top issue in audio communication and conferencing systems. For example, in the ICASSP 2022 Deep Noise Suppression challenge, the improvement in the background and overall quality is impressive, but the improvement in the speech signal is statistically zero. To improve the speech signal the following speech impairment areas must be addressed: coloration, discontinuity, loudness, and reverberation. A dataset and test set were provided for the challenge, and the winners were determined using an extended crowdsourced implementation of ITU-T P.80's listening phase . The results show significant improvement was made across all measured dimensions of speech quality

Programmable Systems for Intelligence in Automobiles (PRYSTINE): Final results after Year 3

Autonomous driving is disrupting the automotive industry as we know it today. For this, fail-operational behavior is essential in the sense, plan, and act stages of the automation chain in order to handle safety-critical situations on its own, which currently is not reached with state-of-the-art approaches.The European ECSEL research project PRYSTINE realizes Fail-operational Urban Surround perceptION (FUSION) based on robust Radar and LiDAR sensor fusion and control functions in order to enable safe automated driving in urban and rural environments. This paper showcases some of the key exploitable results (e.g., novel Radar sensors, innovative embedded control and E/E architectures, pioneering sensor fusion approaches, AI-controlled vehicle demonstrators) achieved until its final year 3

Measurements of azimuthal anisotropies at forward and backward rapidity with muons in high-multiplicity p–Pb collisions at √sNN = 8.16 TeV

The study of the azimuthal anisotropy of inclusive muons produced in p-Pb collisions at sNN−−−√=8.16 TeV, using the ALICE detector at the LHC is reported. The measurement of the second-order Fourier coefficient of the particle azimuthal distribution, v2, is performed as a function of transverse momentum pT in the 0-20% high-multiplicity interval at both forward (2.032 GeV/c. The v2 coefficient of inclusive muons is extracted using two different techniques, namely two-particle cumulants, used for the first time for heavy-flavour measurements, and forward-central two-particle correlations. Both techniques give compatible results. A positive v2 is measured at both forward and backward rapidities with a significance larger than 4.7σ and 7.6σ, respectively, in the interval 2<pT<6 GeV/c. Comparisons with previous measurements in p-Pb collisions at sNN−−−√=5.02 TeV, and with AMPT and CGC-based theoretical calculations are discussed. The findings impose new constraints on the theoretical interpretations of the origin of the collective behaviour in small collision systems

Measurement of ψ(2S) production as a function of charged-particle pseudorapidity density in pp collisions at √s = 13 TeV and p–Pb collisions at √sNN = 8.16 TeV with ALICE at the LHC

Production of inclusive charmonia in pp collisions at center-of-mass energy of s√ = 13 TeV and p-Pb collisions at center-of-mass energy per nucleon pair of sNN−−−√ = 8.16 TeV is studied as a function of charged-particle pseudorapidity density with ALICE. Ground and excited charmonium states (J/ψ, ψ(2S)) are measured from their dimuon decays in the interval of rapidity in the center-of-mass frame 2.5<ycms<4.0 for pp collisions, and 2.03<ycms<3.53 and −4.46<ycms<−2.96 for p-Pb collisions. The charged-particle pseudorapidity density is measured around midrapidity (|η|<1.0). In pp collisions, the measured charged-particle multiplicity extends to about six times the average value, while in p-Pb collisions at forward (backward) rapidity a multiplicity corresponding to about three (four) times the average is reached. The ψ(2S) yield increases with the charged-particle pseudorapidity density. The ratio of ψ(2S) over J/ψ yield does not show a significant multiplicity dependence in either colliding system, suggesting a similar behavior of J/ψ and ψ(2S) yields with respect to charged-particle pseudorapidity density. Results for the ψ(2S) yield and its ratio with respect to J/ψ agree with available model calculations

Measurement of the angle between jet axes in Pb–Pb collisions at √sNN = 5.02 TeV

This letter presents the first measurement of the angle between different jet axes (denoted as ΔR) in Pb−Pb collisions. The measurement is carried out in the 0−10% most-central events at sNN−−−√=5.02 TeV. Jets are assembled by clustering charged particles at midrapidity using the anti-kT algorithm with resolution parameters R=0.2 and 0.4 and transverse momenta in the intervals 40<pchjetT<140 GeV/c and 80<pchjetT<140 GeV/c, respectively. Measurements at these low transverse momenta enhance the sensitivity to quark−gluon plasma (QGP) effects. A comparison to models implementing various mechanisms of jet energy loss in the QGP shows that the observed narrowing of the Pb−Pb distribution relative to pp can be explained if quark-initiated jets are more likely to emerge from the medium than gluon-initiated jets. These new measurements discard intra-jet pT broadening as described in a model calculation with the BDMPS formalism as the main mechanism of energy loss in the QGP. The data are sensitive to the angular scale at which the QGP can resolve two independent splittings, favoring mechanisms that incorporate incoherent energy loss

Observation of flow angle and flow magnitude fluctuations in Pb–Pb collisions at √sNN = 5.02 TeV at the CERN Large Hadron Collider

This Letter reports on the first measurements of transverse momentum dependent flow angle Ψn and flow magnitude vn fluctuations, determined using new four-particle correlators. The measurements are performed for various centralities in Pb-Pb collisions at a centre-of-mass energy per nucleon pair of sNN−−−√ = 5.02 TeV with ALICE at the CERN Large Hadron Collider. Both flow angle and flow magnitude fluctuations are observed in the presented centrality ranges and are strongest in the most central collisions and for a transverse momentum pT>2 GeV/c. Comparison with theoretical models, including iEBE-VISHNU, MUSIC, and AMPT, show that the measurements exhibit unique sensitivities to the initial state of heavy-ion collisions