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UAI
1996
15 years 5 months ago
Bayesian Learning of Loglinear Models for Neural Connectivity
This paper presents a Bayesian approach to learning the connectivity structure of a group of neurons from data on configuration frequencies. A major objective of the research is t...
Kathryn B. Laskey, Laura Martignon
119
Voted
NIPS
1990
15 years 5 months ago
Learning to See Rotation and Dilation with a Hebb Rule
Previous work (M.I. Sereno, 1989; cf. M.E. Sereno, 1987) showed that a feedforward network with area V1-like input-layer units and a Hebb rule can develop area MT-like second laye...
Martin I. Sereno, Margaret E. Sereno
NIPS
1992
15 years 5 months ago
Some Solutions to the Missing Feature Problem in Vision
In visual processing the ability to deal with missing and noisy information is crucial. Occlusions and unreliable feature detectors often lead to situations where little or no dir...
Subutai Ahmad, Volker Tresp
WCE
2007
15 years 5 months ago
Metaplanning Model Based in an Organizational Memory
— When problems are present in production, equipment or the process which are critical for organizations, many management personnel and experts have to meet to propose a solution...
José Bernardo Parra Victorino, Raúl ...
AVSS
2009
IEEE
15 years 5 months ago
Object Tracking from Unstabilized Platforms by Particle Filtering with Embedded Camera Ego Motion
Visual tracking with moving cameras is a challenging task. The global motion induced by the moving camera moves the target object outside the expected search area, according to th...
Carlos R. del-Blanco, Narciso N. García, Lu...
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