Monthly Archives: décembre 2022

Evaluation of neuromorphic AI with embedded Spiking Neural Networks

Edge AI is a recent subject of research that needs to take into account the cost of the neural models both during the training and during the prediction. An original and promising solution to face these constraints is to merge compression technics of deep neural networks and event-based encoding of information thanks to Spiking neural networks (SNN). SNN are considered as third generation of artificial neural networks and are inspired from the way the information is encoded in the brain, and previous works tend to
conclude that SNN are more efficient than classical deep networks. This internship project aims at confirming this assumption by converting classical CNN to SNN from standard Machine Learning frameworks (Keras) and deploy the resulting neural models onto the Akida neuromorphic processor from BrainChip company.

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Development of a prototype HW platform for embedded object detection with bio-inspired retinas

The goal of this internship project is to deploy this spike-based AI solution onto an embedded smart camera provided by the Prophesee company. The camera is composed of an event-based sensor and an FPGA. The work will mainly consist in deploying the existing software code (in C) on the embedded CPU, integrate the HW accelerator (VHDL) onto the FPGA and make the communication between them through an AXI-STREAM bus. The last part of the project will consist in realizing experimentations of the resulting smart cameras to evaluate the real-time performances and energy consumption before a validation onto a driving vehicle.

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