This paper investigates an approach to model the space of brain images through a low-dimensional manifold. A data driven method to learn a manifold from a collections of brain imag...
Samuel Gerber, Tolga Tasdizen, Sarang C. Joshi, Ro...
In this paper, we propose a novel manifold alignment method by learning the underlying common manifold with supervision of corresponding data pairs from different observation sets...
Deming Zhai, Bo Li, Hong Chang, Shiguang Shan, Xil...
In recent years manifold methods have attracted a considerable amount of attention in machine learning. However most algorithms in that class may be termed “manifold-motivatedâ€...
Learning based super-resolution can recover high resolution image with high quality. However, building an interactive learning based super-resolution system for general images is e...
This paper investigates the appearance manifold of facial expression: embedding image sequences of facial expression from the high dimensional appearance feature space to a low dim...