The POSEIDON project aims at defining solutions for scalable CF-mMIMO operating in the sub-6GHz frequencybands where the available spectral resources are scarce. In particular, scalable CF-mMIMO architectures must beable to handle i) to support the dramatic increase in wireless traffic demand, which is caused by the exponentialgrowth of connected w...
Effective recognition of spatial patterns and learning their hierarchy is crucial in modern spatial data analysis. Volumetric data applications seek techniques ensuring invariance not only to shifts but also to pattern rotations. While traditional methods can readily achieve translational invariance, rotational invariance possesses multiple challen...
Channel estimation plays an important role in underwater acoustic communications, with applications in phase-coherent modulation schemes and preparation of replay channels. Quantifying the estimation error is a challenge, however, as the true channel remains unknown. This paper introduces the channel replay error (CRE) as the difference between a t...
Miniaturized CMOS hyperspectral cameras utilizing Fabry-Perot Interferometers (FPIs) have emerged as a low-cost solution providing fast-acquisition miniaturized sensors well-suited for both in-field analysis and remote sensing. However, FPIs generate harmonics around each wavelength of interest, hindering the accuracy and reliability of spectral in...
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...
