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Exploiting Deep Structure

2005
Blurring an image with a Gaussian of width σ and considering σ as an extra dimension, extends the image to an Gaussian scale space ($\mathcal{GSS}$) image. In this $\mathcal{GSS}$-image the iso-intensity manifolds behave in an nicely pre-determined manner.
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Structural Deep Network Embedding

Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2016
Network embedding is an important method to learn low-dimensional representations of vertexes in networks, aiming to capture and preserve the network structure. Almost all the existing network embedding methods adopt shallow models. However, since the underlying network structure is complex, shallow models cannot capture the highly non-linear network ...
Daixin Wang   +2 more
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On topological deep-structure segmentation

Proceedings of International Conference on Image Processing, 2002
A hierarchical segmentation model is obtained by using linear scale evolution of gray-scale images. At each scale segments are generated as Voronoi diagrams with a distance measure defined on the image landscape. The set of centers of the Voronoi cells is the set of local extrema of the gray-scale image.
Stiliyan Kalitzin   +2 more
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The deep structure of business processes

Communications of the ACM, 2006
Delving beneath organizational surface structure to reveal the essential structure of business processes.
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Deep structure as logical form

Synthese, 1970
A transformational derivationof a sentence is a sequence of labeled phrase structure trees. The last tree in the sequence represents the surface structureof the sentence. The first tree represents the deep structureof the sentence.1Each later tree is derived from its predecessor via the application of exactly one transformational rule.
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The deep structure of Derbyshire

Geological Journal, 1985
AbstractPre‐Carboniferous basement beneath Derbyshire is disposed in two southwest‐dipping tilt blocks (Eyam and Woo Dale Blocks), which are separated by a major north‐dipping growth fault (the Bakewell Fault). The surface expression of the Bakewell Fault is largely concealed by late Dinantian carbonate shelf sediments, but its position and trend ...
K. Smith, N. J. P. Smith, D. W. Holliday
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Deep template-based protein structure prediction

PLoS Computational Biology, 2021
Jinbo Xu, Fandi Wu
exaly  

LiZn(OH)CO3: A Deep‐Ultraviolet Nonlinear Optical Hydroxycarbonate Designed from a Diamond‐like Structure

Angewandte Chemie - International Edition, 2021
Pifu Gong, Xiaomeng Liu, Zheshuai Lin
exaly  

Antibody structure prediction using interpretable deep learning

Patterns, 2022
Jeffrey J Gray   +2 more
exaly  

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