A Parallel Face Detection System Implemented on FPGA. - Nicolas Farrugia; Franck Mamalet; Sébastien Roux; Fan Yang 019; Michel Paindavoine (ISCAS, 2007)

Multiple modular very long instruction word processors based on field programmable gate arrays. - Vincent Brost; Fan Yang 019; Michel Paindavoine; Nicolas Farrugia (J. Electronic Imaging, 2007)

Design of a Real-Time Face Detection Parallel Architecture Using High-Level Synthesis. - Nicolas Farrugia; Franck Mamalet; Sébastien Roux; Fan Yang 019; Michel Paindavoine (EURASIP J. Embed. Syst., 2008)

Fast and Robust Face Detection on a Parallel Optimized Architecture Implemented on FPGA. - Nicolas Farrugia; Franck Mamalet; Sébastien Roux; Fan Yang 019; Michel Paindavoine (IEEE Trans. Circuits Syst. Video Technol., 2009)

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)

Incremental learning on chip. - Ghouthi Boukli Hacene; Vincent Gripon; Nicolas Farrugia; Matthieu Arzel; Michel Jézéquel (GlobalSIP, 2017)

Evaluating graph signal processing for neuroimaging through classification and dimensionality reduction. - Mathilde Ménoret; Nicolas Farrugia; Bastien Pasdeloup; Vincent Gripon (GlobalSIP, 2017)

Transfer Incremental Learning using Data Augmentation. - Ghouthi Boukli Hacene; Vincent Gripon; Nicolas Farrugia; Matthieu Arzel; Michel Jézéquel (CoRR, 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)

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 (CAIP Workshops, 2019)

Spectral Graph Wavelet Transform as Feature Extractor for Machine Learning in Neuroimaging. - Yusuf Yigit Pilavci; Nicolas Farrugia (ICASSP, 2019)

Efficient Hardware Implementation of Incremental Learning and Inference on Chip. - Ghouthi B. Hacene; Vincent Gripon; Nicolas Farrugia; Matthieu Arzel; Michel Jézéquel (NEWCAS, 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)

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 (J. Signal Process. Syst., 2019)

Lightweight Convolutional Neural Networks on Binaural Waveforms for Low Complexity Acoustic Scene Classification. - Nicolas Pajusco; Richard Huang; Nicolas Farrugia (DCASE, 2020)

Quantized Guided Pruning for Efficient Hardware Implementations of Deep Neural Networks. - Ghouthi Boukli Hacene; Vincent Gripon; Matthieu Arzel; Nicolas Farrugia; Yoshua Bengio (NEWCAS, 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)

Few-shot Learning for Decoding Brain Signals. - Myriam Bontonou; Nicolas Farrugia; Vincent Gripon (CoRR, 2020)

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 (ACSCC, 2021)

Few-Shot Decoding of Brain Activation Maps. - Myriam Bontonou; Giulia Lioi; Nicolas Farrugia; Vincent Gripon (EUSIPCO, 2021)

Graph-LDA: Graph Structure Priors to Improve the Accuracy in Few-Shot Classification. - Myriam Bontonou; Nicolas Farrugia; Vincent Gripon (CoRR, 2021)

Interdisciplinary approaches for Neurosciences, Artificial Intelligence and Sound. - Nicolas Farrugia (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 (EUSIPCO, 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)

Supervised Contrastive Learning for Respiratory Sound Classification. - Ilyass Moummad; Nicolas Farrugia (CoRR, 2022)

Deep learning models of cognitive processes constrained by human brain connectomes. - Yu Zhang 115; Nicolas Farrugia; Pierre Bellec (Medical Image Anal., 2022)

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 (ICASSP, 2023)

Pretraining Respiratory Sound Representations using Metadata and Contrastive Learning. - Ilyass Moummad; Nicolas Farrugia (WASPAA, 2023)

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

Regularized Contrastive Pre-training for Few-shot Bioacoustic Sound Detection. - Ilyass Moummad; Romain Serizel; Nicolas Farrugia (CoRR, 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)

Mixture of Mixups for Multi-label Classification of Rare Anuran Sounds. - Ilyass Moummad; Nicolas Farrugia; Romain Serizel; Jeremy Froidevaux; Vincent Lostanlen (EUSIPCO, 2024)

Unsupervised Adaptive Deep Learning Method for BCI Motor Imagery Decoding. - Yassine El Ouahidi; Giulia Lioi; Nicolas Farrugia; Bastien Pasdeloup; Vincent Gripon (EUSIPCO, 2024)

Self-Supervised Learning for Few-Shot Bird Sound Classification. - Ilyass Moummad; Nicolas Farrugia; Romain Serizel (ICASSP Workshops, 2024)

Domain-Invariant Representation Learning of Bird Sounds. - Ilyass Moummad; Romain Serizel; Emmanouil Benetos; Nicolas Farrugia (CoRR, 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., 2024)

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, 2025)