ICCV
2011
IEEE
12 years 4 months ago
2011
IEEE
Interpreting an image as a function on a compact subset of the Euclidean plane, we get its scale-space by diffusion, spreading the image over the entire plane. This generates a 1-...
JISE
2010
12 years 11 months ago
2010
In dealing with large datasets the reduced support vector machine (RSVM) was proposed for the practical objective to overcome the computational difficulties as well as to reduce t...
PPSN
2010
Springer
13 years 2 months ago
2010
Springer
Abstract. Taking inspiration from approximate ranking, this paper investigates the use of rank-based Support Vector Machine as surrogate model within CMA-ES, enforcing the invarian...
APGV
2008
ACM
13 years 6 months ago
2008
ACM
The glare illusion is commonly used in CG rendering, especially in game engines, to achieve a higher brightness than that of the maximum luminance of a display. In this work, we m...
SCALESPACE
2001
Springer
13 years 8 months ago
2001
Springer
Receptive field sensitivity profiles of visual front-end cells in the LGN and V1 area in intact animals can be measured with increasing accuracy, both in the spatial and temporal...
ICANN
2007
Springer
13 years 10 months ago
2007
Springer
This paper proposes a novel approach for directly tuning the gaussian kernel matrix for one class learning. The popular gaussian kernel includes a free parameter, σ, that requires...
ICIP
2006
IEEE
14 years 6 months ago
2006
IEEE
Piecewise constant and piecewise smooth Mumford-Shah (MS) models have been widely studied and used for image segmentation. More complicated than piecewise constant MS, global Gaus...
ICIP
2008
IEEE
14 years 6 months ago
2008
IEEE
Kernel PCA has received a lot of attention over the past years and showed usefull for many image processing problems. In this paper we analyse the issue of normalization in Kernel...
CVPR
2007
IEEE
14 years 6 months ago
2007
IEEE
Kernel methods have been widely studied in the field of pattern recognition. These methods implicitly map, "the kernel trick," the data into a space which is more approp...