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Artificial Intelligence at the Edge with Toradex SoMs, Gyrfalcon, Xnor.ai, Movidius and more



Charbax

Toradex https://toradex.com/ is focused on simplifying the integration of these technologies into products with its System on Modules. Typical deep learning models are trained on high-performance computers with frameworks like TensorFlow, so optimizations are needed to improve performance on low-power embedded Linux devices. Toradex’s partnerships with Au-Zone, Xnor.ai and Antmicro can simplify this.

Implementing these dedicated neural network accelerators can boost the performance of embedded devices while keeping power consumption low, as shown in Toradex’s solutions with Intel Movidius Myriad and Gryfalcon Lightspeeur.

Toradex partners with Allied Vision to showcase the brand-new Alvium industrial MIPI CSI-2 camera as a crucial component in the pasta detection demo which uses an Apalis System on Module (https://www.toradex.com/computer-on-modules) featuring the NXP i.MX 8 QuadMax SoC with Cortex-A72, Cortex-A53 and dual OpenCL-capable GPU. To learn more about the demo, see the blog (https://www.cnx-software.com/2019/02/05/adding-machine-learning-image-processing-embedded-product/). A real-world application example of deep learning is Manta, a camera-based drowning detection system from Coral Detection Systems which is solar-powered, and the video analytics are done on a Toradex Apalis module featuring a NVIDIA TK1 SoC with a CUDA-enabled GPU. If a person is at risk of drowning, the system can alert its user acoustically or via smartphone.

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Filmed in 4K60 at Embedded World 2019 with Panasonic G9 ($1133 at https://amzn.to/2EuaQJX) with 12-60mm Leica ($900 at https://amzn.to/2VzFJU7) all my G9 videos are added here: https://www.youtube.com/playlist?list=PL7xXqJFxvYvg_F9pR7IxXwy5bmcErqGeW

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