Ripeness Classification of Cacao Using Cepstral-Based Statistical Features and Support Vector Machine
Author:
Affiliation:
1. College of Engineering and Technology, Cor Jesu College, Inc.,Digos City,Philippines
2. School of Electrical, Electronics and Computer Engineering, Mapua University,Manila,Philippines
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9936688/9936734/09936807.pdf?arnumber=9936807
Reference18 articles.
1. Integrating NIR Spectroscopy and Electronic Tongue Together with Chemometric Analysis for Accurate Classification of Cocoa Bean Varieties
2. Measurement of ripening speed and determination of the optimum ripeness of melons by a nondestructive acoustic vibration method
3. Machine learning algorithm validation with a limited sample size
4. Sample size planning for classification models
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