Difference between revisions of "ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 1"

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Revision as of 14:44, 7 September 2020

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NeuralNetwork.png Applies to Machine Learning
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History[edit | edit source]

Version Date Notes
1.0.0 September 2020 First public release

Introduction[edit | edit source]

This Technical Note (TN for short) is the first one of a series illustrating how machine learning-based inference applications perform across different embedded platforms, which are eligible for building intelligent edge devices.

The idea is to develop one or more applications with the help of well-known open-source frameworks/libraries and to deploy them on such platforms to compare performances, resource utilization, development flow, etc.

Test application #1: fruit classifier[edit | edit source]

This application implements a classifier like the one described here. There is one notable difference, however. In this case, the model was created from scratch using TBD.

Model creation[edit | edit source]