Non-destructive classification of watermelon ripeness using Mel-frequency cepstrum coefficients and multilayer perceptrons

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Non-destructive classification of watermelon ripeness using Mel-frequency cepstrum coefficients and multilayer perceptrons

We present a non-destructive watermelon classification method using Mel-Frequency Cepstrum Coefficients (MFCC) and Multi-Layer Perceptron (MLP) neural network. Acoustic signals were collected from thumping noises of ripe and unripe watermelon fruits. MFCC was then used to convert the signals into MF...

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Bibliographic Details
Published in:	Proceedings of the International Joint Conference on Neural Networks
Main Author:	M. Shah Baki S.R.; Mohd Z. M.A.; Yassin I.M.; Hasliza A.H.; Zabidi A.
Format:	Conference paper
Language:	English
Published:	Institute of Electrical and Electronics Engineers Inc. 2010
Online Access:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-79959444098&doi=10.1109%2fIJCNN.2010.5596573&partnerID=40&md5=b896d16986e0067924cbaf41657c7478

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