Deep learning and support vector machine for effective plant identification
Journal
Proceedings of ICT Innovations 2015 Conference Web Proceedings
Date Issued
2015
Author(s)
Strezoski, Gjorgji
Stojanovski, Dario
Madjarov, Gjorgji
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.
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.
Subjects
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