Detection of damaged wheat kernels using an impact acoustic signal processing technique based on Gaussian modelling and an improved extreme learning machine algorithm

Volume: 184, Pages: 37 - 44
Published: Aug 1, 2019
Abstract
Wheat kernel damage is a major source of food quality degradation, and long-term feeding on products from damaged wheat kernels will result in malnutrition or even induce diseases. Therefore, detection of damaged wheat kernels is of significant interest. An impact acoustic signal processing technique based on Gaussian modelling and an improved extreme learning machine approach was proposed for detection of insect and sprout-damaged wheat...
Paper Details
Title
Detection of damaged wheat kernels using an impact acoustic signal processing technique based on Gaussian modelling and an improved extreme learning machine algorithm
Published Date
Aug 1, 2019
Volume
184
Pages
37 - 44
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