Startup aims to improve efficiency of deep neural networks for image analysis and facial recognition - Biometric Update

January 30, 2018 -

Purdue University-affiliated startup FWDNXT has developed a low-power mobile coprocessor for accelerating image recognition and classification by deep neural networks, Purdue News reports.

The accelerator is called Snowflake, and running on a Field Programmable Gate Array module it can achieve 91 percent computational efficiency on entire convolutional...

via www.biometricupdate.com

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