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AAAI
2006
15 years 4 months ago
Active Learning with Near Misses
Assume that we are trying to build a visual recognizer for a particular class of objects--chairs, for example--using existing induction methods. Assume the assistance of a human t...
Nela Gurevich, Shaul Markovitch, Ehud Rivlin
145
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JMM2
2006
167views more  JMM2 2006»
15 years 2 months ago
Computer Vision Methods for Improved Mobile Robot State Estimation in Challenging Terrains
External perception based on vision plays a critical role in developing improved and robust localization algorithms, as well as gaining important information about the vehicle and ...
Annalisa Milella, Giulio Reina, Roland Siegwart
WSC
2007
15 years 4 months ago
Visual exploration and evaluation of climate-related simulation data
Large, heterogeneous volumes of simulation data are calculated and stored in many disciplines, e.g. in climate and climate impact research. To gain insight, current climate analys...
Thomas Nocke, Michael Flechsig, Uwe Böhm
JMLR
2010
125views more  JMLR 2010»
14 years 9 months ago
Continuous Time Bayesian Network Reasoning and Learning Engine
We present a continuous time Bayesian network reasoning and learning engine (CTBN-RLE). A continuous time Bayesian network (CTBN) provides a compact (factored) description of a co...
Christian R. Shelton, Yu Fan, William Lam, Joon Le...
IIE
2007
120views more  IIE 2007»
15 years 2 months ago
Words are Silver, Mouse-Clicks are Gold? (or how to optimize the level of language formalization of young students in a Logo-bas
How do we teach children to express and communicate ideas in a formal and informal mode? What type of language do they need in a concrete context? How should they determine a prope...
Evgenia Sendova, Toni Chehlarova, Pavel Boytchev