Lessons Learned from the Deployment of Deep Learning Applications in Edge Devices

Edge applications have tough, widely varying requirements. Danon shares lessons learned from three real-world applications in which Hailo’s deep learning processor is being used to implement deep learning.

First, he examines a video analytics use case, where multiple video streams are processed at the edge in real-time. Processing performance demands are substantial, and power consumption is a key constraint. Next, he explores an industrial inspection application, where visual inspection informs the control of physical devices, resulting in a need for low latency. Finally, he presents a smart cities application, where network bandwidth is a key constraint, driving the need for processing near the sensor.

See here for a PDF of the slides.

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