Leaf-based species recognition using convolutional neural networks

Pires, Willian Oliveira; Fernandes, Ricardo Corso; Paula Filho, Pedro Luiz de; Candido Junior, Arnaldo; Teixeira, João Paulo

http://hdl.handle.net/10198/24653

Use this identifier to reference this record.

Name:	Description:	Size:	Format:
Leaf-BasedSpeciesRecognitionUs.pdf.pdf		1.71 MB	Adobe PDF	Download

Send Feedback

Authors

Pires, Willian Oliveira

Fernandes, Ricardo Corso

Paula Filho, Pedro Luiz de

Candido Junior, Arnaldo

Teixeira, João Paulo

Abstract(s)

Identifying plant species is an important activity in specie control and preservation. The identification process is carried out mainly by botanists, consisting of a comparison of already known specimens or using the aid of books, manuals or identification keys. Artificial Neural Networks have been shown to perform well in classification problems and are a suitable approach for species identification. This work uses Convolutional Neural Networks to classify tree species by leaf images. In total, 29 species were collected. This work analyzed two network models, Darknet-19 and GoogLeNet (Inception-v3), presenting a comparison between them. The Darknet and GoogLeNet models achieved recognition rates of 86.2% and 90.3%, respectively.

Keywords

Leaf recognition Tree classification

URI

http://hdl.handle.net/10198/24653

Citation

Pires, Willian Oliveira; Fernandes, Ricardo Corso; Paula Filho, Pedro Luiz de; Candido Junior, Arnaldo; Teixeira, João Paulo (2021). Leaf-based species recognition using convolutional neural networks. In 1st International Conference on Optimization, Learning Algorithms and Applications, OL2A 2021. p. 367-380. ISBN 978-3-030-91884-2