Recognition of Bean Plants in Weeds Using Neural Networks

Abstract

The implementation of a random subspace classifier (RSC) neural network for the recognition of bean plants in weeds was proposed. The RSC neural classifier is based on the multilayer perceptron with a single layer of training connections, allowing a high speed training. The input of this classifier can be considered in various modes, for example, histograms of brightness, contrast, and orientation of micro contours. The RSC neural classifier has been developed for recognition and is applied to different tasks such as micromechanics, tissue recognition, and recognition of metallic textures. The RSC application can help automatize the industrial processes in agriculture. For this purpose, the computer vision based on neural networks can be used.