39,535 research outputs found
Cross-Domain Image Retrieval with Attention Modeling
With the proliferation of e-commerce websites and the ubiquitousness of smart
phones, cross-domain image retrieval using images taken by smart phones as
queries to search products on e-commerce websites is emerging as a popular
application. One challenge of this task is to locate the attention of both the
query and database images. In particular, database images, e.g. of fashion
products, on e-commerce websites are typically displayed with other
accessories, and the images taken by users contain noisy background and large
variations in orientation and lighting. Consequently, their attention is
difficult to locate. In this paper, we exploit the rich tag information
available on the e-commerce websites to locate the attention of database
images. For query images, we use each candidate image in the database as the
context to locate the query attention. Novel deep convolutional neural network
architectures, namely TagYNet and CtxYNet, are proposed to learn the attention
weights and then extract effective representations of the images. Experimental
results on public datasets confirm that our approaches have significant
improvement over the existing methods in terms of the retrieval accuracy and
efficiency.Comment: 8 pages with an extra reference pag
Roman domination number of Generalized Petersen Graphs P(n,2)
A on a graph is a function
satisfying the condition that every vertex
with is adjacent to at least one vertex with . The
of a Roman domination function is the value . The minimum weight of a Roman dominating function on a graph is
called the of , denoted by . In
this paper, we study the {\it Roman domination number} of generalized Petersen
graphs P(n,2) and prove that .Comment: 9 page
A Large-field J=1-0 Survey of CO and Its Isotopologues Toward the Cassiopeia A Supernova Remnant
We have conducted a large-field simultaneous survey of CO, CO,
and CO emission toward the Cassiopeia A (Cas A) supernova
remnant (SNR), which covers a sky area of . The
Cas giant molecular cloud (GMC) mainly consists of three individual clouds with
masses on the order of . The total mass derived from the
emission of the GMC is 2.1 and is
9.5 from the emission. Two regions with
broadened (67 km s) or asymmetric CO line profiles are found
in the vicinity (within a 10 region) of the Cas A SNR, indicating
possible interactions between the SNR and the GMC. Using the GAUSSCLUMPS
algorithm, 547 CO clumps are identified in the GMC, 54 of which are
supercritical (i.e. ). The mass spectrum of the molecular
clumps follows a power-law distribution with an exponent of . The
pixel-by-pixel column density of the GMC can be fitted with a log-normal
probability distribution function (N-PDF). The median column density of
molecular hydrogen in the GMC is cm and half the mass
of the GMC is contained in regions with H column density lower than
cm, which is well below the threshold of star
formation. The distribution of the YSO candidates in the region shows no
agglomeration.Comment: 24 pages, 18 figure
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