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Publications associées (45)

Filter-Informed Spectral Graph Wavelet Networks for Multiscale Feature Extraction and Intelligent Fault Diagnosis

Intelligent fault diagnosis has been increasingly improved with the evolution of deep learning (DL) approaches. Recently, the emerging graph neural networks (GNNs) have also been introduced in the field of fault diagnosis with the goal to make better use o ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Dual-frequency spectral radar retrieval of snowfall microphysics: a physics-driven deep-learning approach

Alexis Berne, Gionata Ghiggi

The use of meteorological radars to study snowfall microphysical properties and processes is well established, in particular via a few distinct techniques: the use of radar polarimetry, of multi-frequency radar measurements, and of the radar Doppler spectr ...

COPERNICUS GESELLSCHAFT MBH2023

Understanding and Visualizing Raw Waveform-based CNNs

Sébastien Marcel, Hannah Muckenhirn

Modeling directly raw waveforms through neural networks for speech processing is gaining more and more attention. Despite its varied success, a question that remains is: what kind of information are such neural networks capturing or learning for different ...

2019

Denoising and Raw-waveform Networks for Weakly-Supervised Gender Identification on Noisy Speech

Mathew Magimai Doss, Jilt Sebastian, Manoj Kumar

This paper presents a raw-waveform neural network and uses it along with a denoising network for clustering in weakly supervised learning scenarios under extreme noise conditions. Specifically, we consider language independent Automatic Gender Recognition ...

ISCA-INT SPEECH COMMUNICATION ASSOC2018

Towards directly modeling raw speech signal for speaker verification using CNNs

Sébastien Marcel, Hannah Muckenhirn

Speaker verification systems traditionally extract and model cepstral features or filter bank energies from the speech signal. In this paper, inspired by the success of neural network-based approaches to model directly raw speech signal for applications su ...

IEEE2018

Gradient-based spectral visualization of CNNs using raw waveforms

Sébastien Marcel, Hannah Muckenhirn

Modeling directly raw waveform through neural networks for speech processing is gaining more and more attention. Despite its varied success, a question that remains is: what kind of information are such neural networks capturing or learning for different t ...

Idiap2018

Characterization of a Piezoelectric AlN Beam Array in Air and Fluid for an Artificial Basilar Membrane

Jongmoon Jang

In this study, we present a piezoelectric artificial basilar membrane (ABM) composed of a 10-channel aluminum nitride beam array. Each beam varies in length from 1306 to 3194 mu m for mimicking the frequency selectivity of the cochlea. To characterize the ...

KOREAN INST METALS MATERIALS2018

Extension of Fourier-based techniques for ultrafast imaging in ultrasound with diverging waves

Jean-Philippe Thiran, Rafael Eduardo Carrillo Rangel, Adrien Georges Jean Besson, Olivier Bernard, Damien Garcia

Ultrafast ultrasound imaging has become an intensive area of research thanks to its capability in reaching high frame rates. In this paper, we propose a scheme which allows the extension of the current Fourier-based techniques derived for planar acquisitio ...

Institute of Electrical and Electronics Engineers2016

Vertex-Frequency Analysis on Graphs

Pierre Vandergheynst, Benjamin Ricaud, David Shuman

One of the key challenges in the area of signal processing on graphs is to design dictionaries and transform methods to identify and exploit structure in signals on weighted graphs. To do so, we need to account for the intrinsic geometric structure of the ...

Academic Press Inc Elsevier Science2016

Delamination monitoring using low frequency stress waves for laminated composites

Wei Shi, Zhisheng Yang, Pingyu Zhu

Owing to the anisotropy of composite laminates, local responses happens at periphery of the drilled hole even under the same loads. The strain measurement is probably the most sensitive and better option to detect and quantify delamination inside composite ...

Politecnico di Milano2016

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