Many of the recently proposed algorithms for learning feature-based ranking functions are based on the pairwise preference framework, in which instead of taking documents in isola...
Vitor R. Carvalho, Jonathan L. Elsas, William W. C...
We present a method for segmenting the parts of multiple instances of a known object category exhibiting large variations in projected shape and colour. The method builds on an ex...
Local invariant feature extraction methods are widely used for image-features matching. There exist a number of approaches aimed at the refinement of the matches between image-fe...
Efficiently detecting outliers or anomalies is an important problem in many areas of science, medicine and information technology. Applications range from data cleaning to clinica...
Matthew Eric Otey, Amol Ghoting, Srinivasan Partha...
Data mining is a new, important and fast growing database application. Outlier (exception) detection is one kind of data mining, which can be applied in a variety of areas like mon...