scholarly journals Incremental Manifold Learning Via Tangent Space Alignment

Author(s):  
Xiaoming Liu ◽  
Jianwei Yin ◽  
Zhilin Feng ◽  
Jinxiang Dong
2016 ◽  
Vol 174 ◽  
pp. 18-30 ◽  
Author(s):  
Qian Wang ◽  
Weiguo Wang ◽  
Rui Nian ◽  
Bo He ◽  
Yue Shen ◽  
...  

2016 ◽  
Vol 2016 ◽  
pp. 1-5 ◽  
Author(s):  
Chuanlei Zhang ◽  
Shanwen Zhang ◽  
Weidong Fang

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.


2011 ◽  
Vol 32 (2) ◽  
pp. 181-189 ◽  
Author(s):  
Peng Zhang ◽  
Hong Qiao ◽  
Bo Zhang

2020 ◽  
Vol 5 (4) ◽  
pp. 6694-6701
Author(s):  
Thomas Cohn ◽  
Odest Chadwicke Jenkins ◽  
Karthik Desingh ◽  
Zhen Zeng

2014 ◽  
Vol 39 (12) ◽  
pp. 2077-2089
Author(s):  
Min YUAN ◽  
Lei CHENG ◽  
Ran-Gang ZHU ◽  
Ying-Ke LEI

Sign in / Sign up

Export Citation Format

Share Document