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» Learning Features by Contrasting Natural Images with Noise
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ICIP
2002
IEEE
14 years 20 days ago
An iterative algorithm for context selection in adaptive entropy coders
Context-based adaptive entropy coding is an essential feature of modern image compression algorithms; however, the design of these coders is non-trivial due to the balance that mu...
Tong Jin, Jacques Vaisey
CVPR
2011
IEEE
13 years 3 months ago
Hyper-graph Matching via Reweighted Random Walks
Establishing correspondences between two feature sets is a fundamental issue in computer vision, pattern recognition, and machine learning. This problem can be well formulated as g...
Jungmin Lee (Seoul National University), Minsu Cho...
IJON
2006
76views more  IJON 2006»
13 years 7 months ago
Joint maps for orientation, eye, and direction preference in a self-organizing model of V1
Primary visual cortex (V1) contains overlaid feature maps for orientation (OR), motion direction selectivity (DR), and ocular dominance (OD). Neurons in these maps are connected l...
James A. Bednar, Risto Miikkulainen
IDA
2008
Springer
13 years 7 months ago
Symbolic methodology for numeric data mining
Currently statistical and artificial neural network methods dominate in data mining applications. Alternative relational (symbolic) data mining methods have shown their effectivene...
Boris Kovalerchuk, Evgenii Vityaev
TIP
2010
255views more  TIP 2010»
13 years 2 months ago
Image Super-Resolution Via Sparse Representation
This paper presents a new approach to single-image superresolution, based on sparse signal representation. Research on image statistics suggests that image patches can be wellrepre...
Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma