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» Recognition Model with Extension Fields
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118
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ROBOCUP
1999
Springer
102views Robotics» more  ROBOCUP 1999»
15 years 4 months ago
A Method for Localization by Integration of Imprecise Vision and a Field Model
In recent years, many researchers in AI and Robotics pay attention to RoboCup, because robotic soccer games needs various techniques in AI and Robotics, such as navigation, behavi...
Kazunori Terada, Kouji Mochizuki, Atsushi Ueno, Hi...
88
Voted
ECCV
2002
Springer
16 years 2 months ago
Factorial Markov Random Fields
In this paper we propose an extension to the standard Markov Random Field (MRF) model in order to handle layers. Our extension, which we call a Factorial MRF (FMRF), is analogous t...
Junhwan Kim, Ramin Zabih
AAAI
2008
15 years 2 months ago
Feature Selection for Activity Recognition in Multi-Robot Domains
In multi-robot settings, activity recognition allows a robot to respond intelligently to the other robots in its environment. Conditional random fields are temporal models that ar...
Douglas L. Vail, Manuela M. Veloso
85
Voted
IVC
2008
100views more  IVC 2008»
15 years 16 days ago
Attention can improve a simple model for object recognition
Object recognition is one of the most important tasks of the visual cortex. Even though it has been closely studied in the field of computer vision and neuroscience, the underlyin...
Edgar Bermudez Contreras, Hilary Buxton, Emmet Spi...
106
Voted
ICML
2007
IEEE
16 years 1 months ago
Dynamic hierarchical Markov random fields and their application to web data extraction
Hierarchical models have been extensively studied in various domains. However, existing models assume fixed model structures or incorporate structural uncertainty generatively. In...
Jun Zhu, Zaiqing Nie, Bo Zhang, Ji-Rong Wen