Category: Image Classification

Data streaming with Arka runtime APIs

The Arka runtime is Megh’s data streaming framework. Arka enables applications to build custom data pipelines spanning multiple devices and accelerators. Low-level details are abstracted away by Arka’s resource manager, which maps an application’s pipeline request to the pool of available hardware. This technology enables low-latency, low-overhead data streaming over complex functional topologies through Arka’s

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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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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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Implementing a CPU-based real-time video analytics pipeline

With growth in available data and computation power, use of video analytics solutions has been growing visibly. Most real-time video analytics use-cases, however, require response times in milliseconds—a level of performance that both CPUs and GPUs cannot always meet when it comes to inference. Here we discuss implementation of a real-time video analytics pipeline on

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Implementing a real-time, deep learning pipeline with Spark Streaming

With the current information age defining the third wave, we are facing an explosion of real-time data, which is in turn increasing demand for real-time analytics. A real-time analytics solution pipeline typically utilizes a streaming library and an analytics platform. Apache Spark is an open-source, distributed computing platform designed to run analytics payloads on a

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