Category:Machine Learning TN
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Machine Learning Services's Technical Notes[edit | edit source]
This is the Technical Notes page for the Machine Learning Services. On this page, you can review ALL available wiki Technical Notes documentation listed in alphabetical order.
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Pages in category "Machine Learning TN"
The following 22 pages are in this category, out of 22 total.
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- MISC-TN-010: Using NXP eIQ Machine Learning Development Environment with Mito8M SoM
- MISC-TN-011: Running an Azure-generated TensorFlow Lite model on Mito8M SoM using NXP eIQ
- MISC-TN-015: Proof-of-Concept of an industrial, high-frame-rate video recording/streaming system
- MISC-TN-022: Advanced controller for DMX / RDM lighting applications
- ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 1
- ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 2
- ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 3
- ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 4
- ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 5
- ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 6
- ML-TN-002 - Real-time Social Distancing estimation
- ML-TN-003 — AI at the edge: visual inspection of assembled PCBs for defect detection — Part 1
- ML-TN-003 — AI at the edge: visual inspection of assembled PCBs for defect detection — Part 2
- ML-TN-003 — AI at the edge: visual inspection of assembled PCBs for defect detection — Part 3
- ML-TN-004 — Machine Learning, spectroscopy, and materials classification
- ML-TN-005 — Real-time Social Distancing and video streaming on Orca SBC
- ML-TN-006 — Keyword Spotting and Asymmetric Multiprocessing on Orca SBC
- ML-TN-007 — AI at the edge: exploring Federated Learning solutions
- ML-TN-008 — AI at the edge: prototyping an IoT real-time endoscope
- ML-TN-009 — AI at the edge: IoT real-time endoscopes and Federated Learning
