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DAGM
2004
Springer
14 years 1 months ago
A Semantic Typicality Measure for Natural Scene Categorization
We propose an approach to categorize real-world natural scenes based on a semantic typicality measure. The proposed typicality measure allows to grade the similarity of an image wi...
Julia Vogel, Bernt Schiele
CVPR
2007
IEEE
14 years 9 months ago
Unsupervised Activity Perception by Hierarchical Bayesian Models
We propose a novel unsupervised learning framework for activity perception. To understand activities in complicated scenes from visual data, we propose a hierarchical Bayesian mod...
Xiaogang Wang, Xiaoxu Ma, Eric Grimson
BMCV
2000
Springer
13 years 12 months ago
The Spectral Independent Components of Natural Scenes
Abstract. We apply independent component analysis (ICA) for learning an efficient color image representation of natural scenes. In the spectra of single pixels, the algorithm was a...
Te-Won Lee, Thomas Wachtler, Terrence J. Sejnowski
AAAI
2012
11 years 10 months ago
A Testbed for Learning by Demonstration from Natural Language and RGB-Depth Video
We are developing a testbed for learning by demonstration combining spoken language and sensor data in a natural real-world environment. Microsoft Kinect RGBDepth cameras allow us...
Young Chol Song, Henry A. Kautz
NIPS
2008
13 years 9 months ago
Natural Image Denoising with Convolutional Networks
We present an approach to low-level vision that combines two main ideas: the use of convolutional networks as an image processing architecture and an unsupervised learning procedu...
Viren Jain, H. Sebastian Seung