522,423 research outputs found
Path, theme and narrative in open plan exhibition settings
Three arguments are made based on the analysis of science exhibitions. First,sufficiently refined techniques of spatial analysis allow us to model the impact oflayout upon visitors' paths, even in moderately sized open plans which allow almostrandom patterns of movement and relatively unobstructed visibility. Second, newlydeveloped or adapted techniques of analysis allow us to make a transition frommodeling the mechanics of spatial movement (the way in which movement is affectedby the distribution of obstacles and boundaries), to modeling the manner in whichmovement might register additional aspects of visual information. Third, theadvantages of such purely spatial modes of analysis extend into providing us with asharper understanding of some of the pragmatic constrains within which exhibitioncontent is conceived and designed
A method to measure a relative transverse velocity of source-lens-observer system using gravitational lensing of gravitational waves
Gravitational waves propagate along null geodesics like light rays in the
geometrical optics approximation, and they may have a chance to suffer from
gravitational lensing by intervening objects, as is the case for
electromagnetic waves. Long wavelength of gravitational waves and compactness
of possible sources may enable us to extract information in the interference
among the lensed images. We point out that the interference term contains
information of relative transverse velocity of the source-lens-observer system,
which may be obtained by possible future space-borne gravitational wave
detectors such as BBO/DECIGO.Comment: 27 pages, 9 figures. Accepted for publication in Physical Review
Cycle-Consistent Deep Generative Hashing for Cross-Modal Retrieval
In this paper, we propose a novel deep generative approach to cross-modal
retrieval to learn hash functions in the absence of paired training samples
through the cycle consistency loss. Our proposed approach employs adversarial
training scheme to lean a couple of hash functions enabling translation between
modalities while assuming the underlying semantic relationship. To induce the
hash codes with semantics to the input-output pair, cycle consistency loss is
further proposed upon the adversarial training to strengthen the correlations
between inputs and corresponding outputs. Our approach is generative to learn
hash functions such that the learned hash codes can maximally correlate each
input-output correspondence, meanwhile can also regenerate the inputs so as to
minimize the information loss. The learning to hash embedding is thus performed
to jointly optimize the parameters of the hash functions across modalities as
well as the associated generative models. Extensive experiments on a variety of
large-scale cross-modal data sets demonstrate that our proposed method achieves
better retrieval results than the state-of-the-arts.Comment: To appeared on IEEE Trans. Image Processing. arXiv admin note: text
overlap with arXiv:1703.10593 by other author
Path, theme and narrative in open plan exhibition settings
Three arguments are made based on the analysis of science exhibitions. First,sufficiently refined techniques of spatial analysis allow us to model the impact oflayout upon visitors' paths, even in moderately sized open plans which allow almostrandom patterns of movement and relatively unobstructed visibility. Second, newlydeveloped or adapted techniques of analysis allow us to make a transition frommodeling the mechanics of spatial movement (the way in which movement is affectedby the distribution of obstacles and boundaries), to modeling the manner in whichmovement might register additional aspects of visual information. Third, theadvantages of such purely spatial modes of analysis extend into providing us with asharper understanding of some of the pragmatic constrains within which exhibitioncontent is conceived and designed
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