Zobrazeno 1 - 10
of 731
pro vyhledávání: '"A. Limonova"'
Recently, in a number of papers it was understood that results on sampling discretization and on the universal sampling discretization can be successfully used in the problem of sampling recovery. Moreover, it turns out that it is sufficient to only
Externí odkaz:
http://arxiv.org/abs/2402.00848
Unfolder: Fast localization and image rectification of a document with a crease from folding in half
Presentation of folded documents is not an uncommon case in modern society. Digitizing such documents by capturing them with a smartphone camera can be tricky since a crease can divide the document contents into separate planes. To unfold the documen
Externí odkaz:
http://arxiv.org/abs/2312.00467
Low-bit quantized neural networks are of great interest in practical applications because they significantly reduce the consumption of both memory and computational resources. Binary neural networks are memory and computationally efficient as they re
Externí odkaz:
http://arxiv.org/abs/2205.09120
Autor:
Trusov, Anton1,2,3 (AUTHOR) dimonstr@iitp.ru, Limonova, Elena1,2 (AUTHOR) vva@smartengines.com, Nikolaev, Dmitry2,4 (AUTHOR), Arlazarov, Vladimir V.1,2 (AUTHOR)
Publikováno v:
Mathematics (2227-7390). Mar2024, Vol. 12 Issue 5, p651. 22p.
This survey addresses sampling discretization and its connections with other areas of mathematics. The survey concentrates on sampling discretization of norms of elements of finite-dimensional subspaces. We present here known results on sampling disc
Externí odkaz:
http://arxiv.org/abs/2109.07567
Autor:
Limonova, I. V.
For a subspace $X$ of functions from $L_2$ we consider the minimal number $m$ of nodes necessary for the exact discretization of the $L_2$-norm of the functions in $X$. We construct a subspace such that for any exact discretization with $m$ nodes the
Externí odkaz:
http://arxiv.org/abs/2104.13731
Publikováno v:
Applied Sciences, Vol 14, Iss 11, p 4664 (2024)
Gaussian filtering, being a convolution with a Gaussian kernel, is a widespread technique in image analysis and computer vision applications. It is the traditional approach for noise reduction. In some cases, performing the exact convolution can be c
Externí odkaz:
https://doaj.org/article/f8cb14c25a6148baacb6e1ccbfc34ff4
Autor:
Limonova, Irina, Temlyakov, Vladimir
We prove a sampling discretization theorem for the square norm of functions from a finite dimensional subspace satisfying Nikol'skii's inequality with an upper bound on the number of sampling points of the order of the dimension of the subspace
Externí odkaz:
http://arxiv.org/abs/2009.10789
One of the most computationally intensive parts in modern recognition systems is an inference of deep neural networks that are used for image classification, segmentation, enhancement, and recognition. The growing popularity of edge computing makes u
Externí odkaz:
http://arxiv.org/abs/2009.07190
Quantized low-precision neural networks are very popular because they require less computational resources for inference and can provide high performance, which is vital for real-time and embedded recognition systems. However, their advantages are ap
Externí odkaz:
http://arxiv.org/abs/2009.06488