ULPEC H2020 Project

Expected outcomes

The goal of ULPEC is to demonstrate a microsystem that is natively brain-inspired, connecting an event-based camera to a dedicated Spiking Neural Network enabled by memristive synapses.

This high-speed, ultra-low power consumption asynchronous visual data processing system will then manipulate the sensor output end-to-end without changing its nature. 

ULPEC targets TRL4, as required by the ICT-03-2016 call, thanks to the functional realization of embedded smart event-based camera.

The system demonstrator aims to prove that the underlying technology is viable and can be used for traffic road events and other applications.

Such a level of integration has never been demonstrated so far, and no commercial equivalent exists on the market. 

The target use case for ULPEC technologies is the vision and recognition of traffic event (signs, obstacles like other cars, persons, etc.) which is part of the major disruption of autonomous and computer assisted driving in the transport and car manufacturing sector. 

Beyond transportation, our long-term vision encompasses all advanced vision applications with ultra-low power requirements and ultra-low latency, as well as for data processing in hardware native neural network.

Fact Sheet

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ULPEC H2020 Project

About ULPEC 

The long term goal of ULPEC is to develop advanced vision applications with ultra-low power requirements and ultra-low latency.

The output of the ULPEC project is a demonstrator connecting a neuromorphic event-based camera to a high speed ultra-low power consumption asynchronous visual data processing system (Spiking Neural Network with memristive synapses).                             

Although the ULPEC device aims to reach TRL 4, it is a highly application-oriented project: prospective use cases will be studied and an application roadmap will be developed, by considering interoperability for an integration in “systems of systems” as well as the definition of upper power consumption limits depending on future application.

The project consortium therefore includes an industrial end-user (Bosch), which will more particularly investigate autonomous and computer assisted driving.

Autonomous and computer assisted driving are indeed a major disruption in the transport and car manufacturing sector.

Vision and recognition of traffic event must be computed with very low latency (to improve security) and low power (to accommodate the power limited environment in a car, such as power budget and heat dissipation). 


January 2017 - December 2020

Project website


Social media

Twitter: https://twitter.com/ULPEC_H2020

LinkedIn:  www.linkedin.com/in/ulpecproject

Google+: https://plus.google.com/u/0/102371682888936829713


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February 8, 2018
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