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==Introduction==
This Technical Note (TN for short) belongs to the series introduced [[ML-TN-001_-_AI_at_the_edge:_comparison_of_different_embedded_platforms_-_Part_1|here]].
In particular, it illustrates the execution of different versions of an inference application (fruit classifier) that makes use of the model described in [[ML-TN-001_-_AI_at_the_edge:_comparison_of_different_embedded_platforms_-_Part_1#Reference_application_.231:_fruit_classifier|this section]], when executed on the [https://www.nxp.com/products/processors-and-microcontrollers/arm-processors/i-mx-applications-processors/i-mx-8-processors/i-mx-8m-plus-arm-cortex-a53-machine-learning-vision-multimedia-and-industrial-iot:IMX8MPLUS NXP i.MX8M Plus EVK]board. In addition, this document compares the results achieved to the ones produced by the platforms that were considered in the i.MX8M-powered [[:Category:Mito8M|Mito8M SoM]] detailed [[ML-TN-001_001 -_AI_at_the_edgeAI at the edge:_comparison_of_different_embedded_platforms_comparison of different embedded platforms -_Part_1#Articles_in_this_seriesPart 2|previous articles of this serieshere]].
Specifically, the following versions of the application were tested:
* Version 1: This version is the same described in [[ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 2|this article]]. As such, inference is implemented in software and is applied to images retrieved from files.
* Version 2: This version is functionally equivalent to the version 1, but it leverages the Neural Processing Unit (NPU) to hardware accelerate the inference.
* Version 3: This is like version 3, but the inference is applied to the frames captured live from an image sensor.
=== Test Bed ===
