Encrypted Internet traffic classification using a supervised Spiking Neural Network

no code implementations • 24 Jan 2021 • Ali Rasteh, Florian Delpech, Carlos Aguilar-Melchor, Romain Zimmer, Saeed Bagheri Shouraki, Timothée Masquelier

Internet traffic recognition is an essential tool for access providers since recognizing traffic categories related to different data packets transmitted on a network help them define adapted priorities.

General Classification Traffic Classification

Low-activity supervised convolutional spiking neural networks applied to speech commands recognition

1 code implementation • 13 Nov 2020 • Thomas Pellegrini, Romain Zimmer, Timothée Masquelier

Deep Neural Networks (DNNs) are the current state-of-the-art models in many speech related tasks.

Technical report: supervised training of convolutional spiking neural networks with PyTorch

2 code implementations • 22 Nov 2019 • Romain Zimmer, Thomas Pellegrini, Srisht Fateh Singh, Timothée Masquelier

Indeed, the most commonly used spiking neuron model, the leaky integrate-and-fire neuron, obeys a differential equation which can be approximated using discrete time steps, leading to a recurrent relation for the potential.