207 citations · 250 across the 5 of their papers we have counts for
5 papers
Real-Time Smart Self-Mixing Interferometry Sensor With Embedded Neural Network
Pierre-Emmanuel Novac, Laurent Rodriguez, Stéphane Barland
Self-mixing interferometry is a measurement ap- proach in which a laser beam is re-injected into the emitting laser itself after reflection on a target. Information about the posit…
Embedded event based object detection with spiking neural network
Jonathan Courtois, Pierre-Emmanuel Novac, Edgar Lemaire +2
The complexity of event-based object detection (OD) poses considerable challenges. Spiking Neural Networks (SNNs) show promising results and pave the way for efficient event-based…
Integrating embedded neural networks and self-mixing interferometry for smart sensors design
Pierre-Emmanuel Novac, Laurent Rodriguez, Stéphane Barland
Self-mixing interferometry is a measurement approach in which a laser beam is re-injected into the emitting laser itself after reflection on a target. Information about the positio…
An Analytical Estimation of Spiking Neural Networks Energy Efficiency
Edgar Lemaire, Loic Cordone, Andrea Castagnetti +3
Spiking Neural Networks are a type of neural networks where neurons communicate using only spikes. They are often presented as a low-power alternative to classical neural networks,…
Quantization and Deployment of Deep Neural Networks on Microcontrollers
Pierre-Emmanuel Novac, Ghouthi Boukli Hacene, Alain Pegatoquet +2
Embedding Artificial Intelligence onto low-power devices is a challenging task that has been partly overcome with recent advances in machine learning and hardware design. Presently…