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» Learning to Recognize Three-Dimensional Objects
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141
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IJCAI
1997
15 years 5 months ago
Object Identification in a Bayesian Context
Object identification—the task of deciding that two observed objects are in fact one and the same object—is a fundamental requirement for any situated agent that reasons about...
Timothy Huang, Stuart J. Russell
130
Voted
ICCV
1995
IEEE
15 years 7 months ago
Fast Object Recognition in Noisy Images Using Simulated Annealing
A fast simulatedannealingalgorithmis developed for automatic object recognition. The object recognition problem is addressed as the problem of best describing a match between a hy...
Margrit Betke, Nicholas C. Makris
123
Voted
MA
1999
Springer
87views Communications» more  MA 1999»
15 years 8 months ago
Communicating Neural Network Knowledge between Agents in a Simulated Aerial Reconnaissance System
In order to maintain their performance in a dynamic environment, agents may be required to modify their learning behavior during run-time. If an agent utilizes a rule-based system...
Stephen Quirolgico, K. Canfield, Timothy W. Finin,...
177
Voted
JMLR
2012
13 years 6 months ago
Online Incremental Feature Learning with Denoising Autoencoders
While determining model complexity is an important problem in machine learning, many feature learning algorithms rely on cross-validation to choose an optimal number of features, ...
Guanyu Zhou, Kihyuk Sohn, Honglak Lee
116
Voted
ICASSP
2009
IEEE
15 years 10 months ago
Connecting spectral and spring methods for manifold learning
Diffusion Maps (DiffMaps) has recently provided a general framework that unites many other spectral manifold learning algorithms, including Laplacian Eigenmaps, and it has become ...
Shannon M. Hughes, Peter J. Ramadge