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» Unsupervised Learning of Image Transformations
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ICPR
2006
IEEE
14 years 11 months ago
Latent Layout Analysis for Discovering Objects in Images
Latent Layout Analysis (LLA) is a novel unsupervised learning technique to discover objects in unseen images using a set of un-annotated training images. LLA defines a generative ...
David Liu, Datong Chen, Tsuhan Chen
ISNN
2004
Springer
14 years 3 months ago
Robust Face Recognition from a Single Training Image per Person with Kernel-Based SOM-Face
In this paper, a kernel-based SOM-face method is proposed to recognize expression variant faces under the situation of only one training image per person. Based on the localization...
Xiaoyang Tan, Songcan Chen, Zhi-Hua Zhou, Fuyan Zh...
ICANN
2005
Springer
14 years 3 months ago
Image Segmentation by Complex-Valued Units
Spike synchronisation and de-synchronisation are important for feature binding and separation at various levels in the visual system. We present a model of complex valued neuron ac...
Cornelius Weber, Stefan Wermter
CVPR
2008
IEEE
14 years 12 months ago
Joint data alignment up to (lossy) transformations
Joint data alignment is often regarded as a data simplification process. This idea is powerful and general, but raises two delicate issues. First, one must make sure that the usef...
Andrea Vedaldi, Gregorio Guidi, Stefano Soatto
IJCV
2008
155views more  IJCV 2008»
13 years 10 months ago
Fast Transformation-Invariant Component Analysis
For software and more illustrations: http://www.psi.utoronto.ca/anitha/fastTCA.htm Dimensionality reduction techniques such as principal component analysis and factor analysis are...
Anitha Kannan, Nebojsa Jojic, Brendan J. Frey