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» Unsupervised Learning of Invariant Features Using Video
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ICANN
2009
Springer
14 years 9 days 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...
ICDM
2010
IEEE
193views Data Mining» more  ICDM 2010»
13 years 5 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
14 years 8 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
14 years 2 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...
ICCV
2005
IEEE
14 years 9 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...