ML-TN-004 — Machine Learning, spectroscopy, and materials classification
Revision as of 12:51, 24 September 2021 by U0001 (talk | contribs) (U0001 moved page ML-TN-003 - Machine Learning, spectroscopy, and material detection to ML-TN-003 — Machine Learning, spectroscopy, and material detection without leaving a redirect)
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HistoryEdit
| Version | Date | Notes |
|---|---|---|
| 1.0.0 | October 2021 | First public release |
IntroductionEdit
Classification and detection of materials is another interesting use case where Machine Learning opens the doors for promising developments related to smart edge devices. In this Technical Note (TN), different embedded platforms
ReferencesEdit
- Hadi Parastara, Geert van Kollenburgb, Yannick Weesepoelc, André van den Doelb, Lutgarde Buydensb, Jeroen Jansen, Integration of handheld NIR and machine learning to “Measure & Monitor” chicken meat authenticity, 2020
- N. Salamati, C. Fredembach, S. Susstrunk, Material Classification Using Color and NIR Images, 2009
- Zackory Erickson, Nathan Luskey, Sonia Chernova, and Charles C. Kemp, Zackory Erickson, Nathan Luskey, Sonia Chernova, and Charles C. Kemp, 2019