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» Unsupervised Learning of Invariant Features Using Video
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86
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ICANN
2009
Springer
15 years 2 months ago
Switching Hidden Markov Models for Learning of Motion Patterns in Videos
Abstract. Building on the current understanding of neural architecture of the visual cortex, we present a graphical model for learning and classification of motion patterns in vid...
Matthias Höffken, Daniel Oberhoff, Marina Kol...
107
Voted
ICDM
2010
IEEE
193views Data Mining» more  ICDM 2010»
14 years 7 months ago
Supervised Link Prediction Using Multiple Sources
Link prediction is a fundamental problem in social network analysis and modern-day commercial applications such as Facebook and Myspace. Most existing research approaches this pro...
Zhengdong Lu, Berkant Savas, Wei Tang, Inderjit S....
ICML
2009
IEEE
15 years 10 months ago
Multi-class image segmentation using conditional random fields and global classification
A key aspect of semantic image segmentation is to integrate local and global features for the prediction of local segment labels. We present an approach to multi-class segmentatio...
Nils Plath, Marc Toussaint, Shinichi Nakajima
WSOM
2009
Springer
15 years 4 months ago
Bag-of-Features Codebook Generation by Self-Organisation
Bag of features is a well established technique for the visual categorisation of objects, categories of objects and textures. One of the most important part of this technique is co...
Teemu Kinnunen, Joni-Kristian Kämärä...
84
Voted
ICCV
2005
IEEE
15 years 11 months ago
Modeling Scenes with Local Descriptors and Latent Aspects
We present a new approach to model visual scenes in image collections, based on local invariant features and probabilistic latent space models. Our formulation provides answers to...
Pedro Quelhas, Florent Monay, Jean-Marc Odobez, Da...