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» Unsupervised feature extraction using neuro-fuzzy approach
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KDD
2003
ACM
195views Data Mining» more  KDD 2003»
16 years 6 months ago
Visualizing changes in the structure of data for exploratory feature selection
Using visualization techniques to explore and understand high-dimensional data is an efficient way to combine human intelligence with the immense brute force computation power ava...
Elias Pampalk, Werner Goebl, Gerhard Widmer
IBPRIA
2009
Springer
15 years 11 months ago
Multi-spectral Texture Characterisation for Remote Sensing Image Segmentation
A multi-spectral texture characterisation model is proposed, the Multi-spectral Local Differences Texem – MLDT, as an affordable approach to be used in multi-spectral images that...
Filiberto Pla, Gema Gracia, Pedro García-Se...
ICDAR
2009
IEEE
16 years 1 months ago
Document Image Retrieval with Local Feature Sequences
In recent years, many document image retrieval algorithms have been proposed. However, most of the current approaches either need good quality images or depend on the page layout ...
Jilin Li, Zhi-Gang Fan, Yadong Wu, Ning Le
ISCAS
2006
IEEE
154views Hardware» more  ISCAS 2006»
16 years 14 days ago
A novel Fisher discriminant for biometrics recognition: 2DPCA plus 2DFLD
— this paper presents a novel image feature extraction and recognition method two dimensional linear discriminant analysis (2DLDA) in a much smaller subspace. Image representatio...
R. M. Mutelo, Li Chin Khor, Wai Lok Woo, Satnam Si...
CVPR
2010
IEEE
15 years 6 months ago
Modeling pixel means and covariances using factorized third-order boltzmann machines
Learning a generative model of natural images is a useful way of extracting features that capture interesting regularities. Previous work on learning such models has focused on me...
Marc Aurelio Ranzato, Geoffrey E. Hinton