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ASIAMS
2007
IEEE
15 years 7 months ago
Rough-Fuzzy Granulation, Rough Entropy and Image Segmentation
This talk has two parts explaining the significance of Rough sets in granular computing in terms of rough set rules and in uncertainty handling in terms of lower and upper approxi...
Sankar K. Pal
111
Voted
CSL
2010
Springer
15 years 1 months ago
From Feasible Proofs to Feasible Computations
We shall discuss several situations in which it is possible to extract from a proof, be it a proof in a first-order theory or a propositional proof, some feasible computational inf...
Jan Krajícek
ISCI
2007
130views more  ISCI 2007»
15 years 17 days ago
Learning to classify e-mail
In this paper we study supervised and semi-supervised classification of e-mails. We consider two tasks: filing e-mails into folders and spam e-mail filtering. Firstly, in a sup...
Irena Koprinska, Josiah Poon, James Clark, Jason C...
106
Voted
ICPR
2006
IEEE
16 years 1 months ago
Illumination Invariant Texture Retrieval
Two fast illumination invariant image retrieval methods for scenes comprising textured objects with variable illumination are introduced. Both methods are based on texture gradien...
Michal Haindl, Pavel Vacha
102
Voted
ICPR
2004
IEEE
16 years 1 months ago
To FRAME or not to FRAME in Probabilistic Texture Modelling?
The maximum entropy principle is a cornerstone of FRAME (Filters, RAndom fields, and Maximum Entropy) model considered at times as a first-ever step towards a universal theory of ...
Georgy L. Gimel'farb, Luc J. Van Gool, Alexey Zale...