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» Learning the Relative Importance of Features in Image Data
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164
Voted
SDM
2011
SIAM
233views Data Mining» more  SDM 2011»
14 years 6 months ago
Multi-Instance Mixture Models
Multi-instance (MI) learning is a variant of supervised learning where labeled examples consist of bags (i.e. multi-sets) of feature vectors instead of just a single feature vecto...
James R. Foulds, Padhraic Smyth
133
Voted
VISAPP
2008
15 years 5 months ago
Continuous Learning of Simple Visual Concepts Using Incremental Kernel Density Estimation
In this paper we propose a method for continuous learning of simple visual concepts. The method continuously associates words describing observed scenes with automatically extracte...
Danijel Skocaj, Matej Kristan, Ales Leonardis
142
Voted
LCPC
2007
Springer
15 years 9 months ago
Modeling Relations between Inputs and Dynamic Behavior for General Programs
Program dynamic optimization, adaptive to runtime behavior changes, has become increasingly important for both performance and energy savings. However, most runtime optimizations o...
Xipeng Shen, Feng Mao
131
Voted
BMCBI
2006
216views more  BMCBI 2006»
15 years 3 months ago
Machine learning approaches to supporting the identification of photoreceptor-enriched genes based on expression data
Background: Retinal photoreceptors are highly specialised cells, which detect light and are central to mammalian vision. Many retinal diseases occur as a result of inherited dysfu...
Haiying Wang, Huiru Zheng, David Simpson, Francisc...
148
Voted
TCSV
2008
291views more  TCSV 2008»
15 years 3 months ago
A Statistical Video Content Recognition Method Using Invariant Features on Object Trajectories
Abstract--This work is dedicated to a statistical trajectorybased approach addressing two issues related to dynamic video content understanding: recognition of events and detection...
Alexandre Hervieu, Patrick Bouthemy, Jean-Pierre L...