Organizing digital images into semantic categories is imperative for effective browsing and retrieval. In large image collections, an efficient algorithm is crucial to quickly cat...
Taufik Abidin, Aijuan Dong, Honglin Li, William Pe...
We investigate how to learn a kernel matrix for high dimensional data that lies on or near a low dimensional manifold. Noting that the kernel matrix implicitly maps the data into ...
Affordable, fast computers with large memories have lessened the demand for program efficiency, but applications such as browsing and searching very large databases often have rat...
We propose simple and fast methods based on nearest neighbors that order objects from high-dimensional data sets from typical points to untypical points. On the one hand, we show ...
Stefan Harmeling, Guido Dornhege, David M. J. Tax,...
Matching local features across images is often useful when comparing or recognizing objects or scenes, and efficient techniques for obtaining image-to-image correspondences have b...