—We study the localization problem in sparse 3D underwater sensor networks. Considering the fact that depth information is typically available for underwater sensors, we transfor...
Wei Cheng, Amin Y. Teymorian, Liran Ma, Xiuzhen Ch...
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
In video surveillance, the sizes of face images are very small. However, few works have been done to investigate scalerobust face recognition. Our experiments on appearancebased m...
The analysis of high-dimensional data is an important, yet inherently difficult problem. Projection techniques such as PCA, MDS, and SOM can be used to map high-dimensional data t...
Tobias Schreck, Tatiana von Landesberger, Sebastia...
In many image retrieval applications, the mapping between highlevel semantic concept and low-level features is obtained through a learning process. Traditional approaches often as...