Sets of local features that are invariant to common image transformations are an effective representation to use when comparing images; current methods typically judge feature set...
This paper addresses the problem of recognizing freeform 3D objects in point clouds. Compared to traditional approaches based on point descriptors, which depend on local informati...
Bertram Drost, Markus Ulrich, Nassir Navab, Slobod...
Although multi-objective GA (MOGA) is an efficient multiobjective optimization (MOO) method, it has some limitations that need to be tackled, which include unguaranteed uniformity...
Ken Harada, Jun Sakuma, Shigenobu Kobayashi, Isao ...
Local ratio is a well-known paradigm for designing approximation algorithms for combinatorial optimization problems. At a very high level, a local-ratio algorithm first decomposes ...
In previous work we developed a method of learning Bayesian Network models from raw data. This method relies on the well known minimal description length (MDL) principle. The MDL ...