Embedding images into a low dimensional space has a wide range of applications: visualization, clustering, and pre-processing for supervised learning. Traditional dimension reduct...
Recent work on unsupervised feature learning has shown that learning on polynomial expansions of input patches, such as on pair-wise products of pixel intensities, can improve the...
Postprocedural analysis of gastrointestinal (GI) endoscopic videos is a difficult task because the videos often suffer from a large number of poor-quality frames due to the motion...
Selen Atasoy, Diana Mateus, Joe Lallemand, Alexand...
ABSTRACT In this paper, we report our experiments using a realworld image dataset to examine the effectiveness of Isomap, LLE and KPCA. The 1,897-image dataset we used consists of ...
Mei-Chen Yeh, I-Hsiang Lee, Gang Wu, Yi Wu, Edward...
Subspace learning techniques are widespread in pattern recognition research. They include PCA, ICA, LPP, etc. These techniques are generally linear and unsupervised. The problem o...