We report on the formal, machine-checked verification of microkernel from an abstract specification down to its C implementation. We assume correctness of compiler, assembly code,...
Gerwin Klein, June Andronick, Kevin Elphinstone, G...
Linear Discriminant Analysis (LDA) is a well-known scheme for supervised subspace learning. It has been widely used in the applications of computer vision and pattern recognition....
The calculation of a low-rank approximation of a matrix is a fundamental operation in many computer vision applications. The workhorse of this class of problems has long been the ...
Stochastic gradient descent (SGD) uses approximate gradients estimated from subsets of the training data and updates the parameters in an online fashion. This learning framework i...
This paper presents a new normalcy model of a scene for change detection using images taken from multiple views and varying illumination conditions. Each coregistered pixel site i...
David B. Cooper, Joseph L. Mundy, Osman Gokhan Sez...