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走調(diào)

A Subpath Kernel for Learning Hierarchical Image Representationssuch kernels have been successfully applied to various domains such as nature language processing and bioinformatics, they mostly concentrate on ordered trees and whose nodes are described by symbolic data. Meanwhile, hierarchical representations have gained increasing interest to describe image con

Intact

NORM

Talkative

Incremental Embedding Within a Dissimilarity-Based Frameworky with a few set of machine learning methods. This last decade has seen majors advancements aiming to link these two fields. The two majors research fields in this direction concern the design of new graph and string kernels and different explicit embedding schemes of structural data. Explicit embed

山崩

A First Step Towards Exact Graph Edit Distance Using Bipartite Graph Matching an optimal assignment of local graph structures which can be established in polynomial time. However, as this approach considers the local structural properties of the graphs only, it yields sub-optimal solutions that overestimate the true edit distance in general. Recently, several attempts for re

過(guò)于光澤

白楊魚

Revisiting Volgenant-Jonker for Approximating Graph Edit Distancerted how the VJ algorithm can be tuned for this task. To this end, we revisit VJ and propose a series of refinements that improve both the speed and memory footprint without sacrificing accuracy in the GED approximation. We quantify the effectiveness of these optimisations by measuring distortion be

neolith

Carbon-Monoxide

Kite Recognition by Means of Graph Matchingle on high-resolution satellite images. Identified at first in the Near East, their area of distribution is getting larger and larger. This wide distribution gives new dimensions in the interpretation of these structures. Consequently, a large scale recognition of kites will help archeologists to un

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