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This presents a direct and simple method to automatically reconstruct the occlusal surface.
We present an approach to automatically reconstruct buildings densely spanning a large urban area.
Software tools were then developed to process this information and automatically reconstruct physiologically accurate 3-D models of neurons and their interconnections.
The UDI framework utilizes a series of novel proximity relationship learning algorithms to automatically reconstruct urban data in a graph database.
In this paper, we propose a method to automatically reconstruct fibres in the whole volume of a muscle from those selectively sampled on the superficial layer.
By means of the iterative equation Xi = Xi−1 + Bi − Ti, it is possible to automatically reconstruct the complete pattern of intersections between neurites and the concentric rings.
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The object is then automatically reconstructed in 3D.
Implement a program that automatically reconstructs the high-level representation from the acquired data type.
An algorithm for automatically reconstructing knot geometries within timber boards is presented, which is based on non-destructive fibre angle measurements on the surface, exploiting the tracheid effect, and on an estimate of the pith location.
The TRDs are automatically reconstructed, the twinning chain trees of the TRDs are determined and represented with fractal graphs, and the ∑3n grain boundaries are identified up to order n = 12.
Since no digital reconstructions of axons have been previously completed for these cell classes, we validated the algorithm by comparing the resulting dendritic arborizations (which were automatically reconstructed along the axons) of the CA1 cells with those available in several public archives.
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