Publications

Signal and Image processing

Looking for Equivalence between Maximum Likelihood and Sparse DOA Estimators (poster)

Direction-of-Arrival estimators depend on the regularization parameter λ which is often empirically tuned. In this work, conducted under the vectorized covariance matrix model, we are looking for theoretical equivalence between the Maximum…

Thomas Aussaguès, Anne Ferréol, Alice Delmer, Pascal Larzabal

EUSIPCO 2024 - 32nd European Signal Processing Conference - 2024

Computer Science

Looking for Equivalence between Maximum Likelihood and Sparse DOA Estimators

Direction-of-Arrival estimators depend on the regularization parameter λ which is often empirically tuned. In this work, conducted under the vectorized covariance matrix model, we are looking for theoretical equivalence between the Maximum…

Thomas Aussaguès, Anne Ferréol, Alice Delmer, Pascal Larzabal

32nd European Signal Processing Conference (EUSIPCO) - 2024

Physics

Enhancing CFRP delamination detection: A Bayesian neural network approach Integrating spatial and temporal information

Non-destructive testing (NDT) plays a pivotal role in ensuring the structural integrity of Carbon Fiber Reinforced Polymers (CFRP). We propose an innovative methodology that leverages spatial and temporal dimensions of thermal imaging data to…

Valentin Noël, Thomas Rodet, Dominique Lesselier

27th International Workshop on Electromagnetic NDE (ENDE-2024) - 2024

Electric power

Aggregation of Battery Energy Storage and Distributed Energy Resources

BESS are key enablers for the implementation of active distribution system functions by providing a range of grid services at the distribution level. This TB describes these grid support services, distributed BESS aggregation approaches, BESS…

Nikos D. Hatziargyriou, G. Joos, Spyros Skarvelis-Kazakos, J. Susanto, T. Offergeld, Υ. Kenarangui, S. Verma, I. Ndiaye, A. Oulis-Rousis, C. Schwaegerl, S. Broderick, J, Reilly, B. Buchholz, K. Yamashita, G. Saridaki, Fabrizio Sossan, M. Valliou, Anne Blavette, H. Evans, L. Fan, H. Wang

Signal and Image processing

Ultrasonic and microwave data fusion for breast imaging within an artificial intelligence context involving a Bayesian approach and transfer learning

Valentin Noël, Thomas Rodet, Dominique Lesselier

2024 IEEE International Symposium on Antennas and Propagation and ITNC-USNC-URSI Radio Science Meeting - 2024

Environmental Engineering

Écoconception en électronique de puissance. Impacts du dimensionnement, de la modularité et de la diagnosticabilité

Design for sustainability in the field of power electronics is gaining momentum, with many concepts yet to be explored and developed. This thesis focuses on a specific aspect of eco-design: circularity, by emphasizing the implementation of…

Briac Baudais

Mathematical Physics

Identification and characterization of damaged fiber-reinforced laminates in a Bayesian framework

Non-destructive thermographic testing of damaged composite laminates modeled from the homogenization of fiber-reinforced polymers is a challenge, both because of its underlying complexity and because of the difficulties encountered in the…

Valentin Noël, Thomas Rodet, Dominique Lesselier

International Journal of Applied Electromagnetics and Mechanics - 2024

Photonic

On-chip light sheet illumination for nanoparticle tracking in microfluidic channels

A simple and inexpensive method is presented to efficiently integrate light sheet illumination in a microfluidic chip for dark-field microscopic tracking and sizing of nanoparticles.

Théo Travers, Gaétan Delhaye, Martinus H. V. Werts, Denis Gindre, Matthieu Loumaigne

Analytical Methods - 2024

Engineering Sciences

Generalized performance criteria for identified models

It is shown that some usual criteria evaluating the performance of an identified model with respect to experimental data, like FIT criterion, can be not well-suited to fast sampled systems. This leads to propose some genralized criteria where the…

Bernard Vau, Henri Bourlès

20th SysID 2024 - IFAC - 2024

Engineering Sciences

Deep-NFA: A deep a contrario framework for tiny object detection

The detection of tiny objects is a challenging task in computer vision. Conventional object detection methods have difficulties in finding the balance between high detection rate and low false alarm rate. In the literature, some methods have…

Alina Ciocarlan, Sylvie Le Hégarat-Mascle, Sidonie Lefebvre, Arnaud Woiselle

Pattern Recognition - 2024