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» Optimizing Learning in Image Retrieval
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DIAL
2006
IEEE
185views Image Analysis» more  DIAL 2006»
14 years 1 months ago
Automatic Content-based Indexing of Digital Documents through Intelligent Processing Techniques
The availability of large, heterogeneous repositories of electronic documents is increasing rapidly, and the need for flexible, sophisticated document manipulation tools is growi...
Floriana Esposito, Stefano Ferilli, Teresa Maria A...
TKDE
2010
224views more  TKDE 2010»
13 years 2 months ago
Non-Negative Matrix Factorization for Semisupervised Heterogeneous Data Coclustering
Coclustering heterogeneous data has attracted extensive attention recently due to its high impact on various important applications, such us text mining, image retrieval, and bioin...
Yanhua Chen, Lijun Wang, Ming Dong
ECCV
2008
Springer
14 years 9 months ago
Compressive Sensing for Background Subtraction
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
IGARSS
2010
13 years 5 months ago
SMOS L1 algorithms
The Level 1 Processing of SMOS transforms the data acquired by MIRAS (Microwave Imaging Radiometer with Aperture Synthesis) into geolocated TOA Brightness Temperatures, providing ...
Antonio Gutierrez, Jose Barbosa, Nuno Catarino, Ri...
ICB
2007
Springer
214views Biometrics» more  ICB 2007»
13 years 11 months ago
Demographic Classification with Local Binary Patterns
LBP (Local Binary Pattern) as an image operator is used to extract LBPH (LBP histogram) features for texture description. In this paper, we present a novel method to use LBPH featu...
Zhiguang Yang, Haizhou Ai