Leaf Image Classification Using Deep Learning Network

Abstract

This paper focuses on leaf cultivar classification, which is a long-established challenge in agricultural artificial intelligence. The difficulties in this task come from the fact that there is large amount of intra-class variability, arising from form changes during the growth of leaves and different physical development, and subtle inter-class differences, originating by belonging to the same species. To cope with this challenging task, we study the possibility of using deep learning techniques for distinguishing leaf cultivars. We employed a soybean leaf cultivar dataset and conducted extensive experiments on it for a comparison study of handcrafted methods and deep learning methods on leaves cultivar recognition tasks. The experimental results indicate the supervisor performance of the deep learning methods over the traditional methods.