Rugged processor boards as inference engines
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By
eeNews Europe
This process was done using trained neural networks from a variety of models such as TensorFlow, MXNet and Caffe to analyze data accurately, quickly and efficiently. The processor boards are tested compliant with the Intel OpenVINO toolkit. This includes a model optimizer tool to facilitate the transition between the training and deployment environment, performs static model analysis, and adjusts the models for optimal execution on the Concurrent Technologies boards.
Concurrent Technologies – www.gocct.com
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