Apprentissage profond

Deep Learning with Embedded Vision

Embedded vision enables a large number of new applications that rely on compact size, low power consumption and low costs. Combining deep learning and cost-effective embedded vision systems can lead to innovative embedded applications. Therefore, much of the deep learning action can and should happen at the edge where smart, connected devices provide faster runtime responses, lower latency and advanced privacy and security.

Basler embedded vision systems for deep learning

At Basler, a dedicated team of hardware and software engineers builds complete deep learning embedded vision solutions. Besides offering a wide variety of high-quality camera modules with different sensors, frame rates and interfaces, we also integrate various high performing edge computing options. Our products work with different processor options from all major manufacturers, namely NXP® and NVIDIA®. For rapid prototyping we also supply you with ready-to-start development kits to accelerate your development.

The advantages of Basler products for embedded deep learning applications are:

  • compact systems due to small form factor

  • lowest system cost due to lean hardware design

  • scalability with different processor options from all major manufacturers

  • industry-proven and long-lasting hardware components

  • easy cloud integration (AWS, MS Azure, Google)

Implementing deep learning – in the cloud or at the edge

No matter which processing unit you choose, Basler offers the driver packages and software you need to get your deep learning application running. We offer easy cloud integration with Amazon Web Services (AWS), Microsoft Azure or Google's cloud platform. Do you want to deploy your artificial neuronal network (ANN) at the edge? No problem! Basler’s embedded vision technology makes it easy to run one or multiple vision systems for deep learning applications at the edge.

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