1,582 research outputs found
Two questions on stable equivalences of Morita type
It is well-known that derived equivalences preserve tensor products and
trivial extensions. We disprove both constructions for stable equivalences of
Morita type.Comment: 9 page
The existence of two non-contractible closed geodesics on every bumpy Finsler compact space form
Let and be a nontrivial element of finite order in
, where the integer , is a finite group which acts
freely and isometrically on the -sphere and therefore is diffeomorphic
to a compact space form. In this paper, we establish first the resonance
identity for non-contractible homologically visible minimal closed geodesics of
the class on every Finsler compact space form when there exist
only finitely many distinct non-contractible closed geodesics of the class
on . Then as an application of this resonance identity, we prove
the existence of at least two distinct non-contractible closed geodesics of the
class on with a bumpy Finsler metric, which improves a result of
Taimanov in [Taimanov 2016] by removing some additional conditions. Also our
results extend the resonance identity and multiplicity results on
in [arXiv:1607.02746] to general compact space forms.Comment: 33 pages, All comments are welcome. arXiv admin note: substantial
text overlap with arXiv:1607.0274
Deep Sketch Hashing: Fast Free-hand Sketch-Based Image Retrieval
Free-hand sketch-based image retrieval (SBIR) is a specific cross-view
retrieval task, in which queries are abstract and ambiguous sketches while the
retrieval database is formed with natural images. Work in this area mainly
focuses on extracting representative and shared features for sketches and
natural images. However, these can neither cope well with the geometric
distortion between sketches and images nor be feasible for large-scale SBIR due
to the heavy continuous-valued distance computation. In this paper, we speed up
SBIR by introducing a novel binary coding method, named \textbf{Deep Sketch
Hashing} (DSH), where a semi-heterogeneous deep architecture is proposed and
incorporated into an end-to-end binary coding framework. Specifically, three
convolutional neural networks are utilized to encode free-hand sketches,
natural images and, especially, the auxiliary sketch-tokens which are adopted
as bridges to mitigate the sketch-image geometric distortion. The learned DSH
codes can effectively capture the cross-view similarities as well as the
intrinsic semantic correlations between different categories. To the best of
our knowledge, DSH is the first hashing work specifically designed for
category-level SBIR with an end-to-end deep architecture. The proposed DSH is
comprehensively evaluated on two large-scale datasets of TU-Berlin Extension
and Sketchy, and the experiments consistently show DSH's superior SBIR
accuracies over several state-of-the-art methods, while achieving significantly
reduced retrieval time and memory footprint.Comment: This paper will appear as a spotlight paper in CVPR201
Two-dimensional finite-difference model for moving boundary hydrodynamic problems
To predict the hydrodynamics of lakes, estuaries and shallow seas, a two 'dimensional
numerical model is developed using the method of fractional steps. The
governing equations, i.e., the vertically integrated Navier-Stokes equations of fluid
motion, are solved through three steps: advection, diffusion and propagation. The
characteristics method is used to solve the advection, the alternating direction implicit
method is applied to compute the diffusion, and the conjugate gradient iterative
method is employed to calculate the propagation. Two ways to simulate
the moving boundary problem are studied. The first method is based on the weir
formulation. The second method is based on the assumption that a thin water layer
exists over the entire dry region at all times. A number of analytical solutions are
used to validate the model. The model is also applied to simulate the wind driven
circulation in Lake Okeechobee, Florida.
(135 page document
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