The global photovoltaic (PV) installed capacity, vital for the electric sector’s decarbonation, reached 1552.3 GWp in 2023. In France, the capacity stood at 19.9 GWp in April 2024. The growth of the PV installed capacity over a year was nearly 32% worldwide and 15.7% in France. However, integrating PV electricity into grids is hindered by poor know...
Accurate Land Surface Temperature (LST) estimation is crucial for understanding environmental dynamics and addressing diverse scientific and societal challenges. This study explores a novel approach for LST estimation using RGB data and integrating it with additional data modalities. By leveraging conditioned Generative Adversarial Networks (cGANs)...
Butterfly Species identification accounts nowadays for a challenge to evaluate the biodiversity state. Using special compact Hyperspectral Cameras for this task is more attractive. Whereas usual techniques use a sequence of images to compute a datacube, we focus here on a single image resulting in a partial butterfly datacube. With a pre identifica...
This article presents a method for binary segmentation of any type of tensor given that a dataset of such tensors with ground truth segmentations is available. The proposed method compresses input tensors through the use of the Discrete Cosine Transform (DCT) followed by a truncation of the resulting spectrums. After the compression step, a shallow...
Signal processing for wireless communications often use a third order Volterra series to model the nonlinear amplifier. Nevertheless, the Saleh model corresponds better to power amplifier device. We optimize the parameters of the Volterra series and derive their analytical expression using the moments of functions of exponential variables. We show ...
Low-Rank Adaptation (LoRA) methods have gained popularity in efficient parameter fine-tuning of models containing hundreds of billions of parameters. In this work, instead, we demonstrate the application of LoRA methods to train small-vision models in Federated Learning (FL) from scratch. We first propose an aggregation-agnostic method to integrate...
This paper presents a completely automatic artifact rejection method for electroencephalographic data based on Riemannian geometry. The proposed method is tested on two P300-based brain-computer interface databases and is shown to allow superior accuracy and information transfer rate as compared to two state-of-the-art methods.
The integration of ultrasound localization microscopy (ULM) in ultrasound imaging has enabled an unprecedented enhancement in resolution, offering insights into blood flow direction and velocity measurement. Despite its potential, ULM remains a complex and time-intensive procedure, continually improved through advancements in deep learning (DL) met...
This paper presents an efficient lossy compression method based on sparse coding for received noisy signals (RX) in satellite communication systems. The emergence of ground station as a service (GSaaS) and centralized radio access net- works (C-RAN) requires efficient data transfers between ground stations and datacenters. Our approach employs spar...
This paper provides an introduction to an intriguing geometric phenomenon that can occur when considering narrowband bivariate signals. This so-called geometric phase may appear when the signal normalized second order instantaneous moment follows a smooth curve in the curved projective space. The resulting geometric phase is independent of the sign...
