kernel canonical correlation analysis (KCCA) is a recently addressed supervised machine learning methods, which shows to be a powerful approach of extracting nonlinear features for...
Abstract This paper proposes a new tree-based ensemble method for supervised classification and regression problems. It essentially consists of randomizing strongly both attribute ...
Appearance-based methods, based on statistical models of the pixel values in an image (region) rather than geometrical object models, are increasingly popular in computer vision. I...
— This work presents an automatic algorithm for extracting vectorial land registers from altimetric data in dense urban areas. We focus on elementary shape extraction and propose...
We propose a new wavelet compression algorithm based on the rate-distortion optimization for densely sampled triangular meshes. Exploiting the normal remesher of Guskov et al., th...