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...
| Published in: | Proceedings of the International Joint Conference on Neural Networks |
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| Main Author: | |
| Format: | Conference paper |
| Language: | English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2010
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| Online Access: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-79959444098&doi=10.1109%2fIJCNN.2010.5596573&partnerID=40&md5=b896d16986e0067924cbaf41657c7478 |