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» Gradient-based learning of higher-order image features
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ICIP
2001
IEEE
14 years 8 months ago
Higher order autocorrelations for pattern classification
The use of higher-order local autocorrelations as features for pattern recognition has been acknowledged since many years, but their applicability was restricted to relatively low...
Vlad Popovici, Jean-Philippe Thiran
ICCV
2011
IEEE
12 years 6 months ago
Gradient-based learning of higher-order image features
Recent work on unsupervised feature learning has shown that learning on polynomial expansions of input patches, such as on pair-wise products of pixel intensities, can improve the...
Roland Memisevic
ICPR
2006
IEEE
14 years 7 months ago
Fast, Illumination Insensitive Face Detection Based on Multilinear Techniques and Curvature Features
This paper brings together two recent developments in image analysis. We consider a new mathematical framework that provides illumination invariant descriptors for face detection....
Christian Bauckhage, Thomas Käster
CVPR
2009
IEEE
15 years 1 months ago
Efficient Kernels for Identifying Unbounded-Order Spatial Features
Higher order spatial features, such as doublets or triplets have been used to incorporate spatial information into the bag-of-local-features model. Due to computational limits, ...
Yimeng Zhang (Carnegie Mellon University), Tsuhan ...
CVPR
2010
IEEE
14 years 2 days ago
Image Retrieval via Probabilistic Hypergraph Ranking
In this paper, we propose a new transductive learning framework for image retrieval, in which images are taken as vertices in a weighted hypergraph and the task of image search is...
Yuchi Huang, Qingshan Liu, Shaoting Zhang, Metaxas...