In this paper we propose a new approach for false positive reduction in the field of mammographic mass detection. The goal is to distinguish between the true recognized masses and ...
We empirically study the relationship between supervised and multiple instance (MI) learning. Algorithms to learn various concepts have been adapted to the MI representation. Howe...
Clustering algorithms typically operate on a feature vector representation of the data and find clusters that are compact with respect to an assumed (dis)similarity measure betwee...
A linear (qd, q, t)-perfect hash family of size s in a vector space V of order qd over a field F of order q consists of a set S = {1, . . . , s} of linear functionals from V to F ...
Many applications need to segment out all small round
regions in an image. This task of finding dots can be viewed
as a region segmentation problem where the dots form one
regio...