Author: Duncan Moss

Megh’s contextual analytics framework

Contextual analytics refers to the use of data analytics methods that take into account the setting in which data is generated, collected, and analyzed. The goal is to provide a more complete and accurate understanding of the data by considering the context in which it was created. In the field of customer behavior analysis, for

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Megh’s continuous AI model training

Continuous training (CT) of artificial intelligence (AI) models refers to the ongoing process of fine tuning pre-trained AI models with new data, allowing them to continually adapt and improve. This approach is used to keep models up to date with the latest information, trends, and patterns. This results in more accurate predictions and decisions from

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Nimble application framework with cross-platform support

With the release of Megh VAS 100 comes a new addition to the Megh Computing solution stack: the Nimble application framework. Nimble is a fast and lightweight service-based framework for implementing CPU, GPU, and FPGA video analytics pipelines. As illustrated below, Nimble sits on top of Arka, Sira, and Deep Learning Engine (DLE), enabling seamless

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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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Megh’s flexible, high-performance deep learning engine

As deep learning (DL) becomes more pervasive, the need for efficient and fast computation is increasing. Traditional central processing units (CPUs) and graphical processing units (GPUs) are typically used for acceleration, despite the limiting nature of their fixed architectures. Field programmable gate arrays (FPGAs) have been highlighted for their flexibility, but until recently have fallen

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