Hybrid Algorithm of Convolutional Neural Networks and Vector Support Machines in Classification

Abstract

Looking for the improvement of the classification, we propose a hybrid algorithm to identify the corn plant and the weed. With the aim of improving the fertilization and herbicide application processes. An efficient process can avoid wasted fertilizers and decrease subsoil contamination. The purpose is to identify the corn plant to specify the fertilizer application in an automated and precise way. Whereas, the identification of the weed allows to apply herbicides directly. In this work we propose a hybrid method with Convolutional Neural Networks (CNN) to extract characteristics from images and Vector Support Machines (SVM) for classification.