Supervised Learning of Large Perceptual Organization: Graph Spectral Partitioning and Learning Automata

Supervised Learning of Large Perceptual Organization: Graph Spectral Partitioning and Learning Automata (2000)

Cached

Download Links

[marathon.csee.usf.edu]

Other Repositories/Bibliography

DBLP

by Sudeep Sarkar , Padmanabhan Soundararajan

Venue:	IEEE Transactions on Pattern Analysis and Machine Intelligence
Citations:	42 - 4 self

BibTeX

@ARTICLE{Sarkar00supervisedlearning,
    author = {Sudeep Sarkar and Padmanabhan Soundararajan},
    title = {Supervised Learning of Large Perceptual Organization: Graph Spectral Partitioning and Learning Automata},
    journal = {IEEE Transactions on Pattern Analysis and Machine Intelligence},
    year = {2000},
    volume = {22},
    pages = {504--525}
}

Years of Citing Articles

Bookmark

OpenURL

Abstract

this article, please send e-mail to: tpami@computer.org, and reference IEEECS Log Number 107780

Citations

5664	Probabilistic Reasoning in Intelligent Systems - Pearl - 1988
3200	Topics in Matrix Analysis - Horn, Johnson - 1994
437	Partitioning sparse matrices with eigenvectors of graphs - Pothen, Simon, et al. - 1990
303	Three-dimensional object recognition from single two-dimensional image - Lowe - 1987
200	An optimal graph theoretic approach to data clustering: Theory and its application to image segmentation - Wu, Leahy - 1993
187	A property of eigenvectors of non-negative symmetric matrices and its application to graph theory - Fiedler - 1975
147	Inferring Global Perceptual Contours from Local Features - Guy, Medioni
143	Learning Automata: An Introduction - Narendra, Thathachar - 1989
121	Structural saliency: The detection of globally salient structures using a locally connected network - Sha’ashua, Ullman - 1988
71	Quantitative measures of change based on feature organization: Eigenvalues and eigenvectors - Sarkar, Boyer - 1996
60	Space and time bounds on indexing 3-d models from 2-d images - Clemens, Jacobs - 1991
60	Using perceptual organization to extract 3-D structures - Mohan, Nevatia - 1989
56	Robust and efficient detection of salient convex groups - Jacobs - 1996
51	A generic grouping algorithm and its quantitative analysis - Amir, Lindenbaum - 1998
50	Integration, inference, and management of spatial information using Bayesian networks: Perceptual organization - Sarkar, Boyer - 1993
33	Learning compatibility coefficients for relaxation labeling processes - Pelillo, Refice - 1994
25	A Framework for Performance Characterization of Intermediate-Level Grouping Modules - Borra, Sarkar - 1997
22	The Combinatorics of Heuristic Search Termination for Object Recognition in Cluttered Environments - Grimson - 1991
20	A Computational Structure for Preattentive Perceptual Organization: Graphical Enumeration and Voting Methods - Sarkar, Boyer - 1994
13	Learning Texture Discrimination Rules in a Multiresolution System," to appear in the special issue on "Learning - Greenspan, Goodman, et al. - 1994
12	Human and Machine Vision: computing perceptual organization. Ellis Horwood - McCafferty - 1990
9	Learning probabilistic appearance models for object recognition - Pope, Lowe - 1996
8	Learning optimal discriminant functions through a cooperative game of automata - Thatachar, Sastry - 1985
8	Learning to Form Large Groups of Salient Image Features - Sarkar - 1998
5	Modelling object recognition as a markov decision process - Draper - 1996
5	Dynamic Edge Warping: An Experimental System for Recovering Disparity - Boyer, Wuescher, et al. - 1991
5	Parameter estimation for optimal object recognition: Theory and application - Li - 1997
4	Hierarchical Image SegmentationDetection of Regular Curves in a Vector Graph - Casadei, Mitter - 1998
4	Figure ground discrimination: A combinatorial optimization method - Herault, Horaud - 1993
4	ªModeling Hypergraphs by Graphs with the Same - Ihler, Wagner, et al. - 1993
3	Using contextual information to set control parameters of a vision process - Houzelle, Fua, et al. - 1994
3	A distributed probabilistic system for adaptive regulation of image processing parameters - Murino, Foresti, et al. - 1996
3	Closed loop object recognition using reinforcement learning - Peng, Bhanu - 1998
3	ªQuantitative Measures of Change Based on Feature Organization: Eigenvalues and Eigenvectors,º - Sarkar, Boyer - 1996
2	ªLow-Level Grouping - Etemadi, Schmidt, et al. - 1991
2	ªLearning and Feature Selection in Stereo Matching,º - Lew, Huang, et al. - 1994
2	ªA Belief Based Approach for Adaptive Image Processing,º Int'l - Murino, Foresti, et al. - 1997
2	ªComputing Contour Closure,º - Elder, Zucker - 1996
2	ªPerceptual Completion of Occluded Surfaces,º - Williams, Hanson - 1994
2	ªFeature-Based Correspondence: An Eigenvector Approach,º - Shapiro, Brady - 1992
2	ªOrganizing Large Structural Modelbases,º - Sengupta, Boyer - 1995
1	ªThe Legacy of Gesalt Psychology,º Scientific Am - Rock, Palmer - 1990
1	ªGeometric Primitive Extraction Using a Genetic Algorithm,º - Roth, Levine - 1994
1	ªLearning Shape Classes,º - Cho, Dunn - 1994
1	ªAdaptive Image Segmentation Using a Genetic Algorithm,º - Bhanu, Lee, et al. - 1995
1	ªNormalized Cuts and Image Segmenation,º - Shi, Malik - 1997
1	ªAlgebraic Connectivity of Graphs,º Czechoslovakian - Fiedler - 1973