Teaching Machines to See

Xilinx Launches reVISION

Kevin Morris, Mar. 14, 2017 – 

The IoT world is all about sensing, and no sense is more important or empowering than vision. We humans rely on our sight to understand the world around us more than any other source of information, and it's likely that the same will be true for our intelligent machines. From automotive applications like ADAS to drones to factory automation, giving our systems the ability to "see" brings capabilities that are difficult or even impossible to achieve in any other way. 

But vision is one of the most challenging computational problems of our era. High-resolution cameras generate massive amounts of data, and processing that information in real time requires enormous computing power. Even the fastest conventional processors are not up to the task, and some kind of hardware acceleration is mandatory at the edge. Hardware acceleration options are limited, however. GPUs require too much power for most edge applications, and custom ASICs or dedicated ASSPs are horrifically expensive to create and don't have the flexibility to keep up with changing requirements and algorithms. 

That makes hardware acceleration via FPGA fabric just about the only viable option. And it makes SoC devices with embedded FPGA fabric - such as Xilinx Zynq and Altera SoC FPGAs - absolutely the solutions of choice. These devices bring the benefits of single-chip integration, ultra-low latency and high bandwidth between the conventional processors and the FPGA fabric, and low power consumption to the embedded vision space. 

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