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» Slow Feature Analysis: Unsupervised Learning of Invariances
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ICML
2004
IEEE
14 years 8 months ago
Training conditional random fields via gradient tree boosting
Conditional Random Fields (CRFs; Lafferty, McCallum, & Pereira, 2001) provide a flexible and powerful model for learning to assign labels to elements of sequences in such appl...
Thomas G. Dietterich, Adam Ashenfelter, Yaroslav B...
ICASSP
2011
IEEE
12 years 11 months ago
A new method for visual stylometry on impressionist paintings
A new emerging field, that of visual stylometry of art, proposes to apply image analysis and machine learning tools to high-resolution digital images of artwork in order to assis...
Hanchao Qi, Shannon Hughes
MLG
2007
Springer
14 years 1 months ago
Weighted Substructure Mining for Image Analysis
1 In web-related applications of image categorization, it is desirable to derive an interpretable classification rule with high accuracy. Using the bag-of-words representation and...
Sebastian Nowozin, Koji Tsuda, Takeaki Uno, Taku K...
BMVC
2010
13 years 5 months ago
Accounting for the Relative Importance of Objects in Image Retrieval
We introduce a method for image retrieval that leverages the implicit information about object importance conveyed by the list of keyword tags a person supplies for an image. We p...
Sung Ju Hwang, Kristen Grauman
ICPR
2008
IEEE
14 years 8 months ago
Audio-visual event classification via spatial-temporal-audio words
In this paper, we propose a generative model-based approach for audio-visual event classification. This approach is based on a new unsupervised learning method using an extended p...
Ming Li, Sanqing Hu, Shih-Hsi Liu, Sung Baang, Yu ...