Difference between revisions of "ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 4"
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==Introduction== | ==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]]. | 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]. The results achieved are also compared to the ones produced by the platforms that were considered in the [[ML-TN-001_-_AI_at_the_edge:_comparison_of_different_embedded_platforms_-_Part_1#Articles_in_this_series|previous articles of this series]]. | |
| + | |||
| + | Specifically, the following versions were tested: | ||
| + | * Version 1: This version is the same described in TBD this article. As such, inference is applied to images retrieved from files . | ||
| + | * Version 2: This version is functionally equivalent to the version 1, but it leverages the NN hardware accelerator. | ||
| + | * Version 3: This is like version 3, but the inference is applied to the frames captured from an image sensor. | ||
Revision as of 13:56, 25 September 2020
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Contents
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) belongs to the series introduced here. In particular, it illustrates the execution of different versions of an inference application (fruit classifier) that makes use of the model described in this section, when executed on the NXP i.MX8M Plus EVK. The results achieved are also compared to the ones produced by the platforms that were considered in the previous articles of this series.
Specifically, the following versions were tested:
- Version 1: This version is the same described in TBD this article. As such, inference is applied to images retrieved from files .
- Version 2: This version is functionally equivalent to the version 1, but it leverages the NN hardware accelerator.
- Version 3: This is like version 3, but the inference is applied to the frames captured from an image sensor.
