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Co-authors

Number of documents

29

Nicolas Farrugia's CV


Journal articles14 documents

  • Majd Abdallah, Nicolas Farrugia, Valentine Chirokoff, Sandra Chanraud. Static and dynamic aspects of cerebro-cerebellar functional connectivity are associated with self-reported measures of impulsivity: A resting-state fMRI study. Network Neuroscience, MIT Press, 2020, 4 (3), pp.891-909. ⟨10.1162/netn_a_00149⟩. ⟨hal-02945181⟩
  • Abdelbasset Brahim, Nicolas Farrugia. Graph Fourier transform of fMRI temporal signals based on an averaged structural connectome for the classification of neuroimaging. Artificial Intelligence in Medicine, Elsevier, 2020, 106, pp.101870. ⟨10.1016/j.artmed.2020.101870⟩. ⟨hal-02945171⟩
  • Natacha Mendes, Sabine Oligschläger, Mark Lauckner, Johannes Golchert, Julia Huntenburg, et al.. A functional connectome phenotyping dataset including cognitive state and personality measures. Scientific Data , Nature Publishing Group, 2019, 6, pp.180307. ⟨10.1038/sdata.2018.307⟩. ⟨hal-02052230⟩
  • Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jezequel. Budget Restricted Incremental Learning with Pre-Trained Convolutional Neural Networks and Binary Associative Memories. Journal of Signal Processing Systems, Springer, 2019, 91 (9), pp.1063-1073. ⟨10.1007/s11265-019-01450-z⟩. ⟨hal-02273161⟩
  • Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jezequel. Transfer Incremental Learning Using Data Augmentation. Applied Sciences, MDPI, 2018, 8 (12), pp.2512. ⟨10.3390/app8122512⟩. ⟨hal-01950211⟩
  • Kelly Jakubowski, Zaariyah Bashir, Nicolas Farrugia, Lauren Stewart. Involuntary and voluntary recall of musical memories: A comparison of temporal accuracy and emotional responses. Memory and Cognition, Springer Verlag, 2018, 46 (5), pp.741 - 756. ⟨10.3758/s13421-018-0792-x⟩. ⟨hal-01875908⟩
  • Simone Dalla Bella, Nicolas Farrugia, Charles-Etienne Benoit, Valentin Bégel, Laura Verga, et al.. BAASTA: Battery for the Assessment of Auditory Sensorimotor and Timing Abilities. Behavior Research Methods, Psychonomic Society, Inc, 2017, 49 (3), pp.1128 - 1145. ⟨10.3758/s13428-016-0773-6⟩. ⟨hal-01771545⟩
  • Simone Dalla Bella, Charles-Etienne Benoit, Nicolas Farrugia, Peter Keller, Hellmuth Obrig, et al.. Gait improvement via rhythmic stimulation in Parkinson’s disease is linked to rhythmic skills. Scientific Reports, Nature Publishing Group, 2017, 7, pp.42005. ⟨10.1038/srep42005⟩. ⟨hal-01771575⟩
  • Kelly Jakubowski, Nicolas Farrugia, Lauren Stewart. Probing imagined tempo for music: Effects of motor engagement and musical experience. Psychology of Music, SAGE Publications, 2016, 44 (6), pp.1274 - 1288. ⟨10.1177/0305735615625791⟩. ⟨hal-01778664⟩
  • Kelly Jakubowski, Nicolas Farrugia, Andrea Halpern, Sathish Sankarpandi, Lauren Stewart. The speed of our mental soundtracks: Tracking the tempo of involuntary musical imagery in everyday life. Memory and Cognition, Springer Verlag, 2015, 43 (8), pp.1229 - 1242. ⟨10.3758/s13421-015-0531-5⟩. ⟨hal-01778665⟩
  • Nicolas Farrugia, Kelly Jakubowski, Rhodri Cusack, Lauren Stewart. Tunes stuck in your brain: The frequency and affective evaluation of involuntary musical imagery correlate with cortical structure. Consciousness and Cognition, Elsevier, 2015, 35, pp.66-77. ⟨10.1016/j.concog.2015.04.020⟩. ⟨hal-01771603⟩
  • Nicolas Farrugia, Franck Mamalet, Sébastien Roux, Fan Yang, Michel Paindavoine. Fast and Robust Face Detection on a Parallel Optimized Architecture implemented on FPGA. IEEE Transactions on Circuits and Systems for Video Technology, Institute of Electrical and Electronics Engineers, 2009, 19 (4), pp.597-602. ⟨hal-00640765⟩
  • Nicolas Farrugia, Franck Mamalet, Sébastien Roux, Fan Yang, Michel Paindavoine. Design of a Real-time face detection parallel architecture using High-Level Synthesis. EURASIP Journal on Embedded Systems, SpringerOpen, 2008, pp.Article ID 928256. ⟨hal-00640773⟩
  • Vincent Brost, Fan Yang, Michel Paindavoine, Nicolas Farrugia. Multiple Modular VLIW Processors based on FPGA. Journal of Electronic Imaging, SPIE and IS&T, 2007, pp.Article ID 24163. ⟨hal-00640783⟩

Conference papers11 documents

  • Ghouthi Boukli Hacene, Vincent Gripon, Matthieu Arzel, Nicolas Farrugia, Yoshua Bengio. Quantized Guided Pruning for Efficient Hardware Implementations of Deep Neural Networks. NEWCAS 2020 : 18th IEEE International New Circuits and Systems Conference, Jun 2020, Montréal, Canada. pp.206-209, ⟨10.1109/NEWCAS49341.2020.9159769⟩. ⟨hal-02934543⟩
  • Yusuf Pilavci, Nicolas Farrugia. Spectral Graph Wavelet Transform as Feature Extractor for Machine Learning in Neuroimaging. ICASSP 2019 : International Conference on Acoustics, Speech, and Signal Processing, May 2019, Brighton, United Kingdom. ⟨10.1109/ICASSP.2019.8683901⟩. ⟨hal-02052244⟩
  • Myriam Bontonou, Carlos Lassance, Vincent Gripon, Nicolas Farrugia. Comparing linear structure-based and data-driven latent spatial representations for sequence prediction. SPIE Optical Engineering + Applications, Aug 2019, San Diego, United States. ⟨10.1117/12.2528450⟩. ⟨hal-02189734⟩
  • Rozenn Nicol, Olivier Dufor, Laetitia Gros, Pascal Rueff, Nicolas Farrugia. EEG measurement of binaural sound immersion. EAA Spatial Audio Signal Processing Symposium, Sep 2019, Paris, France. pp.73-78, ⟨10.25836/sasp.2019.21⟩. ⟨hal-02275183⟩
  • Nicolas Farrugia. Perception et imagerie mentale musicale : que peut nous dire la musique sur le fonctionnement du cerveau ?. 3èmes Journées Perception Sonore, Université de Bretagne Occidentale; Société Française d'Acoustique, Jun 2017, Brest, France. ⟨hal-01559181⟩
  • Vincent Gripon, Ghouthi Boukli Hacene, Nicolas Farrugia, Matthieu Arzel, Michel Jezequel. Incremental learning on chip. 2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP), Nov 2017, Montreal, France. ⟨10.1109/GlobalSIP.2017.8309068⟩. ⟨hal-01875912⟩
  • Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jezequel. Finding All Matches in a Database using Binary Neural Networks. COGNITIVE 2017 : The Ninth International Conference on Advanced Cognitive Technologies and Applications, Feb 2017, Athènes, Greece. pp.59 - 64. ⟨hal-01522646⟩
  • Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jezequel. Budget Restricted Incremental Learning with Pre-Trained Convolutional Neural Networks and Binary Associative Memories. SIPS 2017 : IEEE International Workshop on Signal Processing Systems, Oct 2017, Lorient, France. pp.1 - 4, ⟨10.1109/SiPS.2017.8109978⟩. ⟨hal-01656152⟩
  • Mathilde Menoret, Nicolas Farrugia, Bastien Pasdeloup, Vincent Gripon. Evaluating Graph Signal Processing for Neuroimaging Through Classification and Dimensionality Reduction. GlobalSIP 2017 : 5th IEEE Global Conference on Signal and Information Processing, Nov 2017, Montreal, Canada. pp.618 - 622, ⟨10.1109/GlobalSIP.2017.8309033⟩. ⟨hal-01761345⟩
  • Tristan Stérin, Nicolas Farrugia, Vincent Gripon. An Intrinsic Difference Between Vanilla RNNs and GRU Models. COGNITIVE 2017 : Ninth International Conference on Advanced Cognitive Technologies and Applications, Feb 2017, Athènes, Greece. pp.76 - 81. ⟨hal-01522887⟩
  • Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jezequel. Incremental Learning on Chip. GlobalSIP 2017 : 5th IEEE Global Conference on Signal and Information Processing, Nov 2017, Montréal, Canada. ⟨10.1109/GlobalSIP.2017.8309068⟩. ⟨hal-01754847⟩

Poster communications1 document

  • Samuel Challéat, Alexis Laforge, Rémi Bénos, Nicolas Farrugia, Clélia Sirami, et al.. Sons et lumières du Haut Vicdessos. La nuit au prisme d'une écologie du son et de la lumière artificielle. Séminaire annuel du LabEx DRIIHM (Dispositif de Recherche Interdisciplinaire sur les Interactions Hommes-Milieux), Oct 2018, Marseille / La Couronne, France. ⟨10.13140/RG.2.2.18803.58409⟩. ⟨hal-01893285⟩

Preprints, Working Papers, ...3 documents

  • Abdelbasset Brahim, Nicolas Farrugia. Graph Fourier Transform of fMRI temporal signals based on an averaged structural connectome for the classification of neuroimaging. 2020. ⟨hal-02302538v2⟩
  • Ghouthi Boukli Hacene, Vincent Gripon, Nicolas Farrugia, Matthieu Arzel, Michel Jezequel. Efficient Hardware Implementation of Incremental Learning and Inference on Chip. 2020. ⟨hal-02487476⟩
  • Ghouthi Boukli Hacene, Vincent Gripon, Matthieu Arzel, Nicolas Farrugia, Yoshua Bengio. Quantized Guided Pruning for Efficient Hardware Implementations of Convolutional Neural Networks. 2018. ⟨hal-01965304⟩