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SIBGRAPI
2006
IEEE
16 years 14 days ago
Improving 2D mesh image segmentation with Markovian Random Fields
Traditional mesh segmentation methods normally operate on geometrical models with no image information. On the other hand, 2D image-based mesh generation and segmentation counterp...
Alex Jesus Cuadros-Vargas, Leandro C. Gerhardinger...
APSEC
2005
IEEE
16 years 2 days ago
Ontology-based Active Requirements Engineering Framework
Software-intensive systems are systems of systems that rely on complex interdependencies among themselves as well as with their operational environment to satisfy the required beh...
Seok Won Lee, Robin A. Gandhi
ICMCS
2005
IEEE
183views Multimedia» more  ICMCS 2005»
16 years 1 days ago
Sports Event Recognition Using Layered HMMS
The recognition of events in video data is a subject of much current interest. In this paper, we address several issues related to this topic. The first one is overfitting when ...
Mark Barnard, Jean-Marc Odobez
SMA
2005
ACM
104views Solid Modeling» more  SMA 2005»
16 years 15 hour ago
Packing a trunk: now with a twist!
In an industry project with a German car manufacturer we are faced with the challenge of placing a maximum number of uniform rigid rectangular boxes in the interior of a car trunk...
Friedrich Eisenbrand, Stefan Funke, Andreas Karren...
CVBIA
2005
Springer
15 years 12 months ago
Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines
Abstract. Markov Random Fields (MRFs) are a popular and wellmotivated model for many medical image processing tasks such as segmentation. Discriminative Random Fields (DRFs), a dis...
Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bi...