Principal Component Analysis (PCA) is a basis transformation to diagonalize an estimate of the covariance matrix of input data and, the new coordinates in the Eigenvector basis ar...
We present an algorithm which allows us to reconstruct a RegionOf-Interest (ROI) from transaxial truncated cone-beam projections. While sometimes it is possible to reconstruct goo...
Abstract. We propose a novel method for addressing the model selection problem in the context of kernel methods. In contrast to existing methods which rely on hold-out testing or t...
Automated line detection is a classical image processing topic with many applications such as road detection in remote images and vessel detection in medical images. Many traditio...
Qin Li, Lei Zhang, Jane You, David Zhang, Prabir B...
Kernel-based trackers aggregate image features within the support of a kernel (a mask) regardless of their spatial structure. These trackers spatially fit the kernel (usually in l...