Difference between revisions of "ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 3"
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==Introduction== | ==Introduction== | ||
| − | This Technical Note (TN for short) | + | 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]]. |
| + | Specifically, it illustrates the execution of an inference application that makes use of the model described in [[ML-TN-001_-_AI_at_the_edge:_comparison_of_different_embedded_platforms_-_Part_1#Test_application_.231:_fruit_classifier|this section]] when executed on the [https://www.xilinx.com/products/boards-and-kits/zcu104.html Xilinx Zynq UltraScale+ MPSoC ZCU104 Evaluation Kit]. 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]]. | ||
Revision as of 14:12, 8 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. Specifically, it illustrates the execution of an inference application that makes use of the model described in this section when executed on the Xilinx Zynq UltraScale+ MPSoC ZCU104 Evaluation Kit. The results achieved are also compared to the ones produced by the platforms that were considered in the previous articles of this series.
