Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12188/23146
Title: Deep learning and support vector machine for effective plant identification
Authors: Strezoski, Gjorgji
Stojanovski, Dario
Dimitrovski, Ivica 
Madjarov, Gjorgji
Keywords: deep learning, SVM, support vector machines, plant images, plantCLEF, CNN
Issue Date: 2015
Journal: Proceedings of ICT Innovations 2015 Conference Web Proceedings
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.
URI: http://hdl.handle.net/20.500.12188/23146
Appears in Collections:Faculty of Computer Science and Engineering: Journal Articles

Files in This Item:
File Description SizeFormat 
deeplrn.pdf18.42 MBAdobe PDFView/Open
Show full item record

Page view(s)

40
checked on Apr 28, 2024

Download(s)

7
checked on Apr 28, 2024

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.