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» Slow Feature Analysis: Unsupervised Learning of Invariances
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ICML
2004
IEEE
15 years 10 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
14 years 1 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
15 years 3 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
14 years 7 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
15 years 10 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 ...