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Plant Leaf Recognition through Local Discriminative Tangent Space Alignment
Joint Authors
Zhang, Chuanlei
Zhang, Shanwen
Fang, Weidong
Source
Journal of Electrical and Computer Engineering
Issue
Vol. 2016, Issue 2016 (31 Dec. 2016), pp.1-5, 5 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-03-16
Country of Publication
Egypt
No. of Pages
5
Main Subjects
Information Technology and Computer Science
Abstract EN
Manifold learning based dimensionality reduction algorithms have been payed much attention in plant leaf recognition as the algorithms can select a subset of effective and efficient discriminative features in the leaf images.
In this paper, a dimensionality reduction method based on local discriminative tangent space alignment (LDTSA) is introduced for plant leaf recognition based on leaf images.
The proposed method can embrace part optimization and whole alignment and encapsulate the geometric and discriminative information into a local patch.
The experiments on two plant leaf databases, ICL and Swedish plant leaf datasets, demonstrate the effectiveness and feasibility of the proposed method.
American Psychological Association (APA)
Zhang, Chuanlei& Zhang, Shanwen& Fang, Weidong. 2016. Plant Leaf Recognition through Local Discriminative Tangent Space Alignment. Journal of Electrical and Computer Engineering،Vol. 2016, no. 2016, pp.1-5.
https://search.emarefa.net/detail/BIM-1108408
Modern Language Association (MLA)
Zhang, Chuanlei…[et al.]. Plant Leaf Recognition through Local Discriminative Tangent Space Alignment. Journal of Electrical and Computer Engineering No. 2016 (2016), pp.1-5.
https://search.emarefa.net/detail/BIM-1108408
American Medical Association (AMA)
Zhang, Chuanlei& Zhang, Shanwen& Fang, Weidong. Plant Leaf Recognition through Local Discriminative Tangent Space Alignment. Journal of Electrical and Computer Engineering. 2016. Vol. 2016, no. 2016, pp.1-5.
https://search.emarefa.net/detail/BIM-1108408
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1108408