Deep Learning for Plant Identification in Natural Environment
Joint Authors
Sun, Yu
Wang, Guan
Zhang, Haiyan
Liu, Yuan
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-05-22
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
Plant image identification has become an interdisciplinary focus in both botanical taxonomy and computer vision.
The first plant image dataset collected by mobile phone in natural scene is presented, which contains 10,000 images of 100 ornamental plant species in Beijing Forestry University campus.
A 26-layer deep learning model consisting of 8 residual building blocks is designed for large-scale plant classification in natural environment.
The proposed model achieves a recognition rate of 91.78% on the BJFU100 dataset, demonstrating that deep learning is a promising technology for smart forestry.
American Psychological Association (APA)
Sun, Yu& Liu, Yuan& Wang, Guan& Zhang, Haiyan. 2017. Deep Learning for Plant Identification in Natural Environment. Computational Intelligence and Neuroscience،Vol. 2017, no. 2017, pp.1-6.
https://search.emarefa.net/detail/BIM-1141079
Modern Language Association (MLA)
Sun, Yu…[et al.]. Deep Learning for Plant Identification in Natural Environment. Computational Intelligence and Neuroscience No. 2017 (2017), pp.1-6.
https://search.emarefa.net/detail/BIM-1141079
American Medical Association (AMA)
Sun, Yu& Liu, Yuan& Wang, Guan& Zhang, Haiyan. Deep Learning for Plant Identification in Natural Environment. Computational Intelligence and Neuroscience. 2017. Vol. 2017, no. 2017, pp.1-6.
https://search.emarefa.net/detail/BIM-1141079
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1141079