Solving Latency Challenges in End-to-End Deep Learning Applications

David Ojika submitted this article for inclusion on the MLOps.org site. Thanks, David!

Intel fellowship recipient David Ojika and graduate research assistant Vahid Daneshmand set out to resolve the problem using specialized vision processors and distributed computing architecture. Their technique, conclusions and future work as they explored end-to-end image analytics with the Intel® Movidius™ Myriad™ 2 vision processing unit (VPU) are examined here.

Read the full article at the Intel AI Academy site.

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