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==Introduction==
This Technical Note (TN for short) is the first one of a series illustrating how machine learning-based inference applications are deployed and perform across different embedded platforms, which are eligible for building intelligent edge devices.
The idea is to develop one or more reference applications with the help of well-known open-source frameworks/libraries and to deploy test them on such platforms to compare for comparing performances, resource utilization, development flow, etc.
In the following sections, these applications are described in more detail.
==Test Reference application #1: fruit classifier==
This application implements a classifier like the one described [[MISC-TN-011:_Running_an_Azure-generated_TensorFlow_Lite_model_on_Mito8M_SoM_using_NXP_eIQ|here]]. There is one notable difference, however, with respect to the linked article. In this case, the model was created from scratch using TBD.
