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Descriptor systems: Expanded descriptor equation and Markov parameters
IEEE Transactions on Automatic Control, 1983Generalized concepts of solvability and conditionability are presented for descriptor systems, and tests are given for these generalized properties. An expression is derived for descriptor system Markov parameters. The notion of "expanded descriptor equation" is presented.
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Meteorological Image Descriptors
2005The objective of this paper is to get a visual characterization of time evolution images, in particular, synoptic maps taken from Meteorology. Preliminary tasks required before image processing are reviewed. Two different types of numerical descriptors are extracted for characterizing the images, the called low level numerical descriptors, and the high
José Luis Crespo +3 more
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Journal of Mathematical Chemistry, 2010
In this paper, we introduce the one-two descriptor. The one-two descriptors is the sum of the vertex contributions such that each pendant vertex contributes 1, each vertex of degree two adjacent to pendant vertex contributes 2, and each vertex of degree higher than two also contributes 2.
Vukičević, Damir +6 more
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In this paper, we introduce the one-two descriptor. The one-two descriptors is the sum of the vertex contributions such that each pendant vertex contributes 1, each vertex of degree two adjacent to pendant vertex contributes 2, and each vertex of degree higher than two also contributes 2.
Vukičević, Damir +6 more
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Pain, 1987
Eighty-five patients suffering from advanced cancer pain were asked to attribute a 'definite value' to 5 key words describing pain by rating them on a visual analogue scale (VAS). The score which the patient attributed to each key word was then correlated with 9 variables obtained through patient monitoring files (sex, age, educational background ...
Marcello, Tamburini +3 more
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Eighty-five patients suffering from advanced cancer pain were asked to attribute a 'definite value' to 5 key words describing pain by rating them on a visual analogue scale (VAS). The score which the patient attributed to each key word was then correlated with 9 variables obtained through patient monitoring files (sex, age, educational background ...
Marcello, Tamburini +3 more
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Hierarchical orthogonalization of descriptors
International Journal of Quantum Chemistry, 1997A novel hierarchical orthogonalization procedure is described for a set of partially ordered molecular descriptors to be used in making statistical correlations within a given data set.
Douglas J. Klein +5 more
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Complementary Keypoint Descriptors
2016We examine the use of complementary descriptors for keypoint recognition in digital images. The descriptors combine multiple types of information, including shape, color, and texture. We first review several keypoint descriptors and propose new descriptors that use normalized brightness/color spatial histograms.
Clark F. Olson +3 more
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1983
This section reviews the molecular shape descriptors developed by Amoore, Allinger, Simon et al. and Testa and Purcell. The illustrative examples discussed refer to the odour similarity and cardiotoxic aglycones. One has stressed the methods based on the reference structure because, correctly formulated, these methods seem to offer promising ...
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This section reviews the molecular shape descriptors developed by Amoore, Allinger, Simon et al. and Testa and Purcell. The illustrative examples discussed refer to the odour similarity and cardiotoxic aglycones. One has stressed the methods based on the reference structure because, correctly formulated, these methods seem to offer promising ...
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2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015
A nested motion descriptor is a spatiotemporal representation of motion that is invariant to global camera translation, without requiring an explicit estimate of optical flow or camera stabilization. This descriptor is a natural spatiotemporal extension of the nested shape descriptor [2] to the representation of motion.
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A nested motion descriptor is a spatiotemporal representation of motion that is invariant to global camera translation, without requiring an explicit estimate of optical flow or camera stabilization. This descriptor is a natural spatiotemporal extension of the nested shape descriptor [2] to the representation of motion.
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Learning General and Distinctive 3D Local Deep Descriptors for Point Cloud Registration
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023Fabio Poiesi, Davide Boscaini
exaly