Nicolas Farrugia

Orcid: 0000-0001-7160-0431

According to our database1, Nicolas Farrugia authored at least 36 papers between 2007 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
Domain-Invariant Representation Learning of Bird Sounds.
CoRR, 2024

Self-Supervised Learning for Few-Shot Bird Sound Classification.
Proceedings of the IEEE International Conference on Acoustics, 2024

Unsupervised Adaptive Deep Learning Method for BCI Motor Imagery Decoding.
Proceedings of the 32nd European Signal Processing Conference, 2024

Mixture of Mixups for Multi-label Classification of Rare Anuran Sounds.
Proceedings of the 32nd European Signal Processing Conference, 2024

2023
Multi-Modal Learning-based Reconstruction of High-Resolution Spatial Wind Speed Fields.
CoRR, 2023

Regularized Contrastive Pre-training for Few-shot Bioacoustic Sound Detection.
CoRR, 2023

A Strong and Simple Deep Learning Baseline for BCI MI Decoding.
CoRR, 2023

Pretraining Representations for Bioacoustic Few-shot Detection using Supervised Contrastive Learning.
CoRR, 2023

Pretraining Respiratory Sound Representations using Metadata and Contrastive Learning.
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.
Proceedings of the IEEE International Conference on Acoustics, 2023

2022
Deep learning models of cognitive processes constrained by human brain connectomes.
Medical Image Anal., 2022

Supervised Contrastive Learning for Respiratory Sound Classification.
CoRR, 2022

Learning-based estimation of in-situ wind speed from underwater acoustics.
CoRR, 2022

Pruning Graph Convolutional Networks to Select Meaningful Graph Frequencies for FMRI Decoding.
Proceedings of the 30th European Signal Processing Conference, 2022

Interdisciplinary approaches for Neurosciences, Artificial Intelligence and Sound.
, 2022

2021
Graph-LDA: Graph Structure Priors to Improve the Accuracy in Few-Shot Classification.
CoRR, 2021

Few-Shot Decoding of Brain Activation Maps.
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?
Proceedings of the 55th Asilomar Conference on Signals, Systems, and Computers, 2021

2020
Few-shot Learning for Decoding Brain Signals.
CoRR, 2020

Graph Fourier transform of fMRI temporal signals based on an averaged structural connectome for the classification of neuroimaging.
Artif. Intell. Medicine, 2020

Quantized Guided Pruning for Efficient Hardware Implementations of Deep Neural Networks.
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.
Proceedings of 5th the Workshop on Detection and Classification of Acoustic Scenes and Events 2020 (DCASE 2020), 2020

2019
Budget Restricted Incremental Learning with Pre-Trained Convolutional Neural Networks and Binary Associative Memories.
J. Signal Process. Syst., 2019

Comparing linear structure-based and data-driven latent spatial representations for sequence prediction.
CoRR, 2019

Efficient Hardware Implementation of Incremental Learning and Inference on Chip.
Proceedings of the 17th IEEE International New Circuits and Systems Conference, 2019

Spectral Graph Wavelet Transform as Feature Extractor for Machine Learning in Neuroimaging.
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.
Proceedings of the Computer Analysis of Images and Patterns, 2019

2018
Quantized Guided Pruning for Efficient Hardware Implementations of Convolutional Neural Networks.
CoRR, 2018

Transfer Incremental Learning using Data Augmentation.
CoRR, 2018

2017
Evaluating graph signal processing for neuroimaging through classification and dimensionality reduction.
Proceedings of the 2017 IEEE Global Conference on Signal and Information Processing, 2017

Incremental learning on chip.
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.
NeuroImage, 2015

2009
Fast and Robust Face Detection on a Parallel Optimized Architecture Implemented on FPGA.
IEEE Trans. Circuits Syst. Video Technol., 2009

2008
Design of a Real-Time Face Detection Parallel Architecture Using High-Level Synthesis.
EURASIP J. Embed. Syst., 2008

2007
Multiple modular very long instruction word processors based on field programmable gate arrays.
J. Electronic Imaging, 2007

A Parallel Face Detection System Implemented on FPGA.
Proceedings of the International Symposium on Circuits and Systems (ISCAS 2007), 2007


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