We present a manifold learning approach to dimensionality
reduction that explicitly models the manifold as a mapping
from low to high dimensional space. The manifold is
represen...
A novel multiregion graph cut image partitioning method combined with kernel mapping is presented. A kernel function transforms implicitly the image data into data of a higher dim...
In many vision problems, rotation-invariant analysis is necessary or preferred. Popular solutions are mainly based on pose normalization or brute-force learning, neglecting the in...
Kun Liu, Qing Wang, Wolfgang Driever, Olaf Ronnebe...
When labeled examples are limited and difficult to obtain, transfer learning employs knowledge from a source domain to improve learning accuracy in the target domain. However, the...
ErHeng Zhong, Wei Fan, Jing Peng, Kun Zhang, Jiang...