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Maximum Flows by Incremental Breadth-First Search

Author(s): Goldberg, Andrew V; Hed, Sagi; Kaplan, Haim; Tarjan, Robert E; Werneck, Renato F

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dc.contributor.authorGoldberg, Andrew V-
dc.contributor.authorHed, Sagi-
dc.contributor.authorKaplan, Haim-
dc.contributor.authorTarjan, Robert E-
dc.contributor.authorWerneck, Renato F-
dc.date.accessioned2021-10-08T19:47:34Z-
dc.date.available2021-10-08T19:47:34Z-
dc.date.issued2011en_US
dc.identifier.citationGoldberg, Andrew V., Sagi Hed, Haim Kaplan, Robert E. Tarjan, and Renato F. Werneck. "Maximum Flows by Incremental Breadth-First Search." In European Symposium on Algorithms (2011): pp. 457-468. doi:10.1007/978-3-642-23719-5_39en_US
dc.identifier.issn0302-9743-
dc.identifier.urihttp://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.450.1652&rep=rep1&type=pdf-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr1254z-
dc.description.abstractMaximum flow and minimum s-t cut algorithms are used to solve several fundamental problems in computer vision. These problems have special structure, and standard techniques perform worse than the special-purpose Boykov-Kolmogorov (BK) algorithm. We introduce the incremental breadth-first search (IBFS) method, which uses ideas from BK but augments on shortest paths. IBFS is theoretically justified (runs in polynomial time) and usually outperforms BK on vision problems.en_US
dc.format.extent457 - 468en_US
dc.language.isoen_USen_US
dc.relation.ispartofEuropean Symposium on Algorithmsen_US
dc.rightsAuthor's manuscripten_US
dc.titleMaximum Flows by Incremental Breadth-First Searchen_US
dc.typeConference Articleen_US
dc.identifier.doi10.1007/978-3-642-23719-5_39-
dc.identifier.eissn1611-3349-
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/conference-proceedingen_US

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