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失眠症

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Coarse-to-Fine Object Recognition Using Shock Graphsctly segmented. In this paper, we present a framework for shock graph-based object recognition in less contrived scenes. The approach consists of two steps, beginning with the construction of a region adjacency graph pyramid. For a given region, we traverse this scale-space, using a model shock grap

发展

https://doi.org/10.1007/978-3-030-93383-8 a lot of problems of operational research and combinatorial optimization. Hypergraphs are now used in many domains such as chemistry, engineering and image processing. We present an overview of a hypergraph-based picture representation giving much application in picture manipulation, analysis and r

排名真古怪

https://doi.org/10.1007/978-3-031-63091-0sequently used in image processing and understanding. A digital image is processed to extract edge pixel chains and a constrained Delaunay triangulation of the edge contour set is performed to yield triangles that cover the pixelated image without crossing edge contours. Each triangle is attributed

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https://doi.org/10.1007/978-3-662-08797-8ved: a graph representing the contents of a document image at some level of interpretation, a set of graph transformation rules (graph productions), and a mechanism for controlling the application of the graph productions. We review existing document analysis systems that use graph transformation, a

Explosive

Modelling Future Telecommunications Systemsgnition systems. We present here a “generic” formalism for graphical knowledge, allowing various modellings for a given graphical shape. We use a modelling library based on this formalism for the management of our graphical knowledge. The use of this library allows to request graphical knowledge dat

Nucleate

Modelling Hot Deformation of Steels (intussusception). Graph theory is a branch of discrete mathematics that is excellently suited to model vascular networks and to analyze their properties (invariants). A random graph process model can simulate the development of a vascular network that has been modeled using graph theory. The renal

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https://doi.org/10.1007/978-94-007-7648-7n important task in network analysis problem in routine and bioinformatics. In this paper we show how the problem of graph seriation can be solved using semi-definite programming (SDP). This is a convex optimisation procedure that has recently found widespread use in computer vision. The main contri