User contributions
11 November 2021
AXEL Lite SOM/AXEL Lite Hardware/Pinout Table
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+637
AXEL Lite SOM/AXEL Lite Hardware/Pinout Table
no edit summary
+311
AXEL Lite SOM/AXEL Lite Hardware/Power and Reset/System boot
no edit summary
+612
AXEL Lite SOM/AXEL Lite Hardware/Power and Reset/System boot
Boot options
+162
AXEL Lite SOM/AXEL Lite Hardware/Power and Reset/Reset scheme and control signals
Reset scheme and control signals
+14
29 September 2021
ML-TN-004 — Machine Learning, spectroscopy, and materials classification
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mMISC-TN-011: Running an Azure-generated TensorFlow Lite model on Mito8M SoM using NXP eIQ
Introduction
+9
24 September 2021
ML-TN-004 — Machine Learning, spectroscopy, and materials classification
NN accelerator: DPU
+17
ML-TN-004 — Machine Learning, spectroscopy, and materials classification
Baseline model
+194
ML-TN-004 — Machine Learning, spectroscopy, and materials classification
Platform: Xilinx Zynq UltraScale+ MPSoC
+933
ML-TN-004 — Machine Learning, spectroscopy, and materials classification
Introduction
+4
ML-TN-004 — Machine Learning, spectroscopy, and materials classification
NN accelerator: DPU
+1,237
ML-TN-004 — Machine Learning, spectroscopy, and materials classification
no edit summary
+19
ML-TN-004 — Machine Learning, spectroscopy, and materials classification
Configuration #2: Xilinx MPSoC + DPU
-42
ML-TN-004 — Machine Learning, spectroscopy, and materials classification
no edit summary
+439
ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 6
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-8
ML-TN-004 — Machine Learning, spectroscopy, and materials classification
no edit summary
-5
ML-TN-004 — Machine Learning, spectroscopy, and materials classification
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mML-TN-004 — Machine Learning, spectroscopy, and materials classification
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+185
ML-TN-004 — Machine Learning, spectroscopy, and materials classification
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mML-TN-004 — Machine Learning, spectroscopy, and materials classification
no edit summary
+25
ML-TN-004 — Machine Learning, spectroscopy, and materials classification
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ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 6
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ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 1
Articles in this series
+184
15 July 2021
MISC-TN-020: Running AWS IoT Greengrass Core version 2 on SBCSPG
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-2
MISC-TN-020: Running AWS IoT Greengrass Core version 2 on SBCSPG
Introduction
+6,228
MISC-TN-020: Running AWS IoT Greengrass Core version 2 on SBCSPG
Introduction
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MISC-TN-020: Running AWS IoT Greengrass Core version 2 on SBCSPG
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14 July 2021
12 July 2021
1 July 2021
MISC-TN-017: Persistent storage and read-write file systems
Embedded Linux systems with eMMC or SD cards
+252
MISC-TN-017: Persistent storage and read-write file systems
no edit summary
+98
30 June 2021
29 June 2021
25 June 2021
MISC-TN-019: Post-portem analysis of embedded Linux systems — Part 1
Introduction
+48
Linux and interrupt latency (Axel)
Introduction
+262
21 June 2021
MISC-TN-019: Post-portem analysis of embedded Linux systems — Part 1
no edit summary
-166
MISC-TN-019: Post-portem analysis of embedded Linux systems — Part 1
Introduction
+119
MISC-TN-019: Post-portem analysis of embedded Linux systems — Part 1
Introduction
+25
MISC-TN-019: Post-portem analysis of embedded Linux systems — Part 1
Introduction
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MISC-TN-019: Post-portem analysis of embedded Linux systems — Part 1
no edit summary
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MISC-TN-019: Post-portem analysis of embedded Linux systems — Part 1
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mMISC-TN-019: Post-portem analysis of embedded Linux systems — Part 1
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MISC-TN-019: Post-portem analysis of embedded Linux systems — Part 1
Created page with "{{InfoBoxTop}} {{AppliesToSBCSPG}} {{InfoBoxBottom}} {{WarningMessage|text=This Technical Note was validated against specific versions of hardware and software. What is descri..."
7 June 2021
ML-TN-003 — AI at the edge: visual inspection of assembled PCBs for defect detection — Part 3
Useful links
-2
ML-TN-003 — AI at the edge: visual inspection of assembled PCBs for defect detection — Part 3
Useful links
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ML-TN-003 — AI at the edge: visual inspection of assembled PCBs for defect detection — Part 3
History
-1
ML-TN-003 — AI at the edge: visual inspection of assembled PCBs for defect detection — Part 3
Results validation
-2
4 June 2021
ML-TN-003 — AI at the edge: visual inspection of assembled PCBs for defect detection — Part 3
Defects generation and acquisition
+115
ML-TN-003 — AI at the edge: visual inspection of assembled PCBs for defect detection — Part 3
Results validation
+1