Azlan Salim, I. Yassin, M. K. A. Mahmood, Z. I. Khan, M. Ali, Khairul Khaizi Mohd Shariff, F. N. Osman, Adizul Ahmad, F. Eskandari
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引用次数: 1
Abstract
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).
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