The performance of many computer vision and machine learning algorithms critically depends on the quality of the similarity measure defined over the feature space. Previous works...
The problem of identifying approximately duplicate objects in databases is an essential step for the information integration process. Most existing approaches have relied on gener...
The issue of ®nding similar 3-D surface segments arises in many recent applications of spatial database systems, such as molecular biology, medical imaging, CAD, and geographic i...
A structural similarity kernel is presented in this paper for SVM learning, especially for learning with imbalanced datasets. Kernels in SVM are usually pairwise, comparing the sim...
The unsupervised nature of cluster analysis means that objects can be clustered in many different ways. This means that different clustering algorithms can lead to vastly different...