The Open Analytics Blog

Megh’s Deep Learning Engine usages

Video analytics use cases Enterprise users are increasingly interested in implementing complex video analytics use cases that provide business value beyond typical applications. These involve multi-stage models for object detection and image classification with custom trained models that are integrated to solve business problems. Some examples include: Segment Use case Deep learning tasks Retail Cashier-less

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September 20, 2020

Implementing a CPU+FPGA-based real-time video analytics pipeline

This post is a follow-up to “Implementing a CPU-based real-time video analytics pipeline,” where we discussed a CPU-based end-to-end video analytics pipeline. As seen in that post, a CPU-based pipeline runs into severe performance bottlenecks. Here we discuss how we address and overcome these bottlenecks using FPGAs as hardware accelerators. We explain Megh’s Video Analytics

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June 22, 2020

Megh’s platform strategy — Part 2

In part 1 (Megh’s platform strategy), we talked about the increasingly rapid explosion of data (from the Web, sensors, IOT devices, etc.), the need for efficient processing, and the value proposition of our real-time streaming analytics platform from the perspective of CIOs, data scientists, and developers. In this post, we discuss how the vendor-agnostic architecture

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April 30, 2020

Megh VAS Beta 1 Release showcases acceleration of deep learning functions

We are excited to announce that the Megh Video Analytics Solution (Megh VAS) Beta 1 Release is available! The Megh VAS Beta 1 Release extends the earlier Megh VAS alpha releases. The alpha releases showcased inline processing of various streams, including filtering and transformations of data. For example, the Megh VAS Alpha Release for Intel

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April 26, 2020

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