NDLI: Minimax entropy and learning by diffusion

Content Provider	IEEE Xplore Digital Library
Author	Shah, J.
Copyright Year	1998
Description	Author affiliation: Dept. of Math., Northeastern Univ., Boston, MA, USA (Shah, J.)
Abstract	A system of coupled differential equations is formulated which learns priors for modelling "preattentive" textures. It is derived from an energy functional consisting of a linear combination of a large number of terms corresponding to the features that the system is capable of learning. The system learns the parameters associated with each feature by applying gradient ascent to the log-likelihood function. Update of each parameter is thus governed by the residual with respect to the corresponding feature. A feature residual is computed from its observed value and value generated by the system. The latter is calculated from a synthesized sample image, which is generated by means of a reaction-diffusion equation obtained by applying gradient descent to the energy functional.
Starting Page	92
Ending Page	97
File Size	834485
Page Count	6
File Format	PDF
ISBN	0818684976
ISSN	10636919
DOI	10.1109/CVPR.1998.698593
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1998-06-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Minimax techniques Entropy Nonlinear equations Differential equations Filters Probability distribution Mathematics Mathematical model Ear Image generation
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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