ECOC-SVM Classification of Coffee Roast Levels based on MNDT s-Parameters
This research describes an intelligent method for differentiating coffee roasting levels based on Microwave Non- Destructive Testing (MNDT) data. The MNDT method collects s-parameter readings from several types of coffee (dark, medium, and light roast) by passing microwaves through them. Error-Corre...
| Published in: | 2022 IEEE 10th Conference on Systems, Process and Control, ICSPC 2022 - Proceedings |
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| Main Author: | |
| Format: | Conference paper |
| Language: | English |
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Institute of Electrical and Electronics Engineers Inc.
2022
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85146693181&doi=10.1109%2fICSPC55597.2022.10001741&partnerID=40&md5=3cd6145f5e8cf7c22bbb16880e748791 |
| Summary: | This research describes an intelligent method for differentiating coffee roasting levels based on Microwave Non- Destructive Testing (MNDT) data. The MNDT method collects s-parameter readings from several types of coffee (dark, medium, and light roast) by passing microwaves through them. Error-Correcting Output Coding Support Vector Machine (ECOC-SVM) was fed a multi-layer perceptron neural network to assess the degree of different coffee roasts. With a small number of hidden units, the ECOC-SVM could identify between the various roasts (with 6,400 data points per sample). © 2022 IEEE. |
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| ISSN: | |
| DOI: | 10.1109/ICSPC55597.2022.10001741 |