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This book presents well researched soft computing techniques geared at improving the characterization speed and accuracy for oil palm fruitlets. The stakes for the production of oil palm industry is on the increase and the sensing and characterization of oil palm fruitlets can no longer be left to traditional handpicking technique. This work therefore explores the pattern classification capability of several softcomputing models to classify oil palm fruitlets using data obtained from laboratory measurements. These measurements include the reflection coefficients from which the dielectric properties of the oil palm fruitlets were extracted. Comparison of the models with industry standards shows that the models are robust, accurate and effective.
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