Deep Learning and Support Vector Machine for Effective Plant Identification

Web proceedings papers

Authors

Gjorgji Strezoski , Dario Stojanovski , Ivica Dimitrovski and Gjorgji Madjarov

Abstract

Our planet is blooming with vegetation that consists of hundreds of thousands of plant species. Each and every one species is unique in its own way, thus enabling people to distinguish one plant from another. Distinguishing plant species is a non trivial task, in fact, it is challenging even for renowned botanists with lots of years of experience in the field. Having in mind the complexity of the task, in this paper we present a system for plant species identification based on Convolutional Neural Networks (CNN’s) and Support Vector Machines (SVM’s). The combination of these two approaches for both feature generation and classification results in a powerful plant identification system. Additionally we report state of the art results using this approach, as well as comparison with other types of approaches on the same dataset.

Keywords

deep learning, SVM, support vector machines, plant images, plantCLEF, CNN