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» Unsupervised learning of visual taxonomies
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PPSN
2004
Springer
14 years 27 days ago
Coupling of Evolution and Learning to Optimize a Hierarchical Object Recognition Model
Abstract. A key problem in designing artificial neural networks for visual object recognition tasks is the proper choice of the network architecture. Evolutionary optimization met...
Georg Schneider, Heiko Wersing, Bernhard Sendhoff,...
FGR
2000
IEEE
161views Biometrics» more  FGR 2000»
13 years 12 months ago
Learning and Synthesizing Human Body Motion and Posture
A novel approach is presented for estimating human body posture and motion from a video sequence. Human pose is defined as the instantaneous image plane configuration of a singl...
Rómer Rosales, Stan Sclaroff
NIPS
2004
13 years 9 months ago
Modeling Nonlinear Dependencies in Natural Images using Mixture of Laplacian Distribution
Capturing dependencies in images in an unsupervised manner is important for many image processing applications. We propose a new method for capturing nonlinear dependencies in ima...
Hyun-Jin Park, Te-Won Lee
CVPR
2012
IEEE
11 years 10 months ago
Robust Boltzmann Machines for recognition and denoising
While Boltzmann Machines have been successful at unsupervised learning and density modeling of images and speech data, they can be very sensitive to noise in the data. In this pap...
Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hi...
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...