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Sparse matrix-based image enhancement for target detection using deep learning
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Paper Abstract

Leaf maturation from initiation to senescence is a phenological event of plants that is a result of the influences of temperature and water availability on physiological activities during a life cycle. Detection of newly grown leaves (NGL) is therefore useful in diagnosis if growth of trees, tree stress and even climatic change. There are many important applications that can naturally be modeled as a low-rank plus a sparse contribution. This paper develop a new algorithm and application to detect NGL. It uses first sparse matrix as a preprocessing to enhance target and applied deep learning to segment the image. The experimental results show that our proposed method can detect targets effectively and decrease false alarm rate.

Paper Details

Date Published: 24 May 2018
PDF: 6 pages
Proc. SPIE 10679, Optics, Photonics, and Digital Technologies for Imaging Applications V, 106791Q (24 May 2018); doi: 10.1117/12.2306744
Show Author Affiliations
Shih-Yu Chen , National Yunlin Univ. of Science and Technology (Taiwan)
Zhe-Yuan Kao, National Yunlin Univ. of Science and Technology (Taiwan)
Fu-Ming Yang , National Yunlin Univ. of Science and Technology (Taiwan)
Yen-Chung Chen , National Yunlin Univ. of Science and Technology (Taiwan)


Published in SPIE Proceedings Vol. 10679:
Optics, Photonics, and Digital Technologies for Imaging Applications V
Peter Schelkens; Touradj Ebrahimi; Gabriel Cristóbal, Editor(s)

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