Monitoring of Bacterial Pustule on Soybean by Neural Network Using Hyperspectral Data

摘要

This paper proposes a technique for estimating the soybean bacterial pustule infection using a neural network, provided with hyperspectral data obtained from the cranemounted hyperspectral sensor system. This technique uses the concept of a quotient set in manifold to reduce the feature space of hyperspectral data. This preliminary study shows that the manifold-embedded neural network is effective to classify bacterial pustule degrees in the nonlinearly reduced hyperspectral feature space.