Nicolas Farrugia

According to our database, Nicolas Farrugia authored at least 38 papers between 2007 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

AutoMashup: Automatic Music Mashups Creation.

Marine Delabaere, Léa Miqueu, Michael Moreno, Gautier Bigois, Hoang Duong, Ella Fernandez, Flavie Manent, Maria Salgado-Herrera, Bastien Pasdeloup, Nicolas Farrugia, Axel Marmoret

CoRR, August, 2025

2024

fMRIStroke: A preprocessing pipeline for fMRI Data from Stroke patients.

Alix Lamouroux, Giulia Lioi, Julie Coloigner, Pierre Maurel, Nicolas Farrugia

J. Open Source Softw., December, 2024

Domain-Invariant Representation Learning of Bird Sounds.

Ilyass Moummad, Romain Serizel, Emmanouil Benetos, Nicolas Farrugia

CoRR, 2024

Self-Supervised Learning for Few-Shot Bird Sound Classification.

Ilyass Moummad, Nicolas Farrugia, Romain Serizel

Proceedings of the IEEE International Conference on Acoustics, 2024

Unsupervised Adaptive Deep Learning Method for BCI Motor Imagery Decoding.

Yassine El Ouahidi, Giulia Lioi, Nicolas Farrugia, Bastien Pasdeloup, Vincent Gripon

Proceedings of the 32nd European Signal Processing Conference, 2024

Mixture of Mixups for Multi-label Classification of Rare Anuran Sounds.

Ilyass Moummad, Nicolas Farrugia, Romain Serizel, Jeremy Froidevaux, Vincent Lostanlen

Proceedings of the 32nd European Signal Processing Conference, 2024

2023

Multi-Modal Learning-based Reconstruction of High-Resolution Spatial Wind Speed Fields.

Matteo Zambra, Nicolas Farrugia, Dorian Cazau, Alexandre Gensse, Ronan Fablet

CoRR, 2023

Regularized Contrastive Pre-training for Few-shot Bioacoustic Sound Detection.

Ilyass Moummad, Romain Serizel, Nicolas Farrugia

CoRR, 2023

A Strong and Simple Deep Learning Baseline for BCI MI Decoding.

Yassine El Ouahidi, Vincent Gripon, Bastien Pasdeloup, Ghaith Bouallegue, Nicolas Farrugia, Giulia Lioi

CoRR, 2023

Pretraining Representations for Bioacoustic Few-shot Detection using Supervised Contrastive Learning.

Ilyass Moummad, Romain Serizel, Nicolas Farrugia

CoRR, 2023

Pretraining Respiratory Sound Representations using Metadata and Contrastive Learning.

Ilyass Moummad, Nicolas Farrugia

Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, 2023

Spatial Graph Signal Interpolation with an Application for Merging BCI Datasets with Various Dimensionalities.

Yassine El Ouahidi, Lucas Drumetz, Giulia Lioi, Nicolas Farrugia, Bastien Pasdeloup, Vincent Gripon

Proceedings of the IEEE International Conference on Acoustics, 2023

2022

Deep learning models of cognitive processes constrained by human brain connectomes.

Yu Zhang, Nicolas Farrugia, Pierre Bellec

Medical Image Anal., 2022

Supervised Contrastive Learning for Respiratory Sound Classification.

Ilyass Moummad, Nicolas Farrugia

CoRR, 2022

Learning-based estimation of in-situ wind speed from underwater acoustics.

Matteo Zambra, Dorian Cazau, Nicolas Farrugia, Alexandre Gensse, Sara Pensieri, Roberto Bozzano, Ronan Fablet

CoRR, 2022

Pruning Graph Convolutional Networks to Select Meaningful Graph Frequencies for FMRI Decoding.

Yassine El Ouahidi, Hugo Tessier, Giulia Lioi, Nicolas Farrugia, Bastien Pasdeloup, Vincent Gripon

Proceedings of the 30th European Signal Processing Conference, 2022

Interdisciplinary approaches for Neurosciences, Artificial Intelligence and Sound.

Nicolas Farrugia

, 2022

2021

Graph-LDA: Graph Structure Priors to Improve the Accuracy in Few-Shot Classification.

Myriam Bontonou, Nicolas Farrugia, Vincent Gripon

CoRR, 2021

Few-Shot Decoding of Brain Activation Maps.

Myriam Bontonou, Giulia Lioi, Nicolas Farrugia, Vincent Gripon

Proceedings of the 29th European Signal Processing Conference, 2021

Similarity between Base and Novel Classes: a Predictor of the Performance in Few-Shot Classification of Brain Activation Maps?

Myriam Bontonou, Nicolas Farrugia, Vincent Gripon

Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020

Few-shot Learning for Decoding Brain Signals.

Myriam Bontonou, Nicolas Farrugia, Vincent Gripon

CoRR, 2020

Graph Fourier transform of fMRI temporal signals based on an averaged structural connectome for the classification of neuroimaging.

Abdelbasset Brahim, Nicolas Farrugia

Artif. Intell. Medicine, 2020

Quantized Guided Pruning for Efficient Hardware Implementations of Deep Neural Networks.

Ghouthi Boukli Hacene, Vincent Gripon, Matthieu Arzel, Nicolas Farrugia, Yoshua Bengio

Proceedings of the 18th IEEE International New Circuits and Systems Conference, 2020

Lightweight Convolutional Neural Networks on Binaural Waveforms for Low Complexity Acoustic Scene Classification.

Nicolas Pajusco, Richard Huang, Nicolas Farrugia

Proceedings of 5th the Workshop on Detection and Classification of Acoustic Scenes and Events 2020 (DCASE 2020), 2020

2019

Comparing linear structure-based and data-driven latent spatial representations for sequence prediction.

Myriam Bontonou, Carlos Eduardo Rosar Kós Lassance, Vincent Gripon, Nicolas Farrugia

CoRR, 2019

Efficient Hardware Implementation of Incremental Learning and Inference on Chip.

Ghouthi B. Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jézéquel

Proceedings of the 17th IEEE International New Circuits and Systems Conference, 2019

Spectral Graph Wavelet Transform as Feature Extractor for Machine Learning in Neuroimaging.

Yusuf Yigit Pilavci, Nicolas Farrugia

Proceedings of the IEEE International Conference on Acoustics, 2019

Classification of Autism Spectrum Disorder Through the Graph Fourier Transform of fMRI Temporal Signals Projected on Structural Connectome.

Abdelbasset Brahim, Mehdi Hajjam El Hassani, Nicolas Farrugia

Proceedings of the Computer Analysis of Images and Patterns, 2019

2018

Quantized Guided Pruning for Efficient Hardware Implementations of Convolutional Neural Networks.

Ghouthi Boukli Hacene, Vincent Gripon, Matthieu Arzel, Nicolas Farrugia, Yoshua Bengio

CoRR, 2018

Transfer Incremental Learning using Data Augmentation.

Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jézéquel

CoRR, 2018

2017

Budget restricted incremental learning with pre-trained convolutional neural networks and binary associative memories.

Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jézéquel

Proceedings of the 2017 IEEE International Workshop on Signal Processing Systems, 2017

Evaluating graph signal processing for neuroimaging through classification and dimensionality reduction.

Mathilde Ménoret, Nicolas Farrugia, Bastien Pasdeloup, Vincent Gripon

Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

Incremental learning on chip.

Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jézéquel

Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

2015

Expectations induced by natural-like temporal fluctuations are independent of attention decrement: Evidence from behavior and early visual evoked potentials.

Gérard Derosière, Nicolas Farrugia, Stéphane Perrey, Tomas E. Ward, Kjerstin Torre

NeuroImage, 2015

2009

Fast and Robust Face Detection on a Parallel Optimized Architecture Implemented on FPGA.

Nicolas Farrugia, Franck Mamalet, Sébastien Roux, Fan Yang, Michel Paindavoine

IEEE Trans. Circuits Syst. Video Technol., 2009

2008

Design of a Real-Time Face Detection Parallel Architecture Using High-Level Synthesis.

Nicolas Farrugia, Franck Mamalet, Sébastien Roux, Fan Yang, Michel Paindavoine

EURASIP J. Embed. Syst., 2008

2007

Multiple modular very long instruction word processors based on field programmable gate arrays.

Vincent Brost, Fan Yang, Michel Paindavoine, Nicolas Farrugia

J. Electronic Imaging, 2007

A Parallel Face Detection System Implemented on FPGA.

Nicolas Farrugia, Franck Mamalet, Sébastien Roux, Fan Yang, Michel Paindavoine

Proceedings of the International Symposium on Circuits and Systems (ISCAS 2007), 2007