Zobrazeno 1 - 10
of 142
pro vyhledávání: '"Arlazarov, Vladimir"'
In this paper, we introduce HoughToRadon Transform layer, a novel layer designed to improve the speed of neural networks incorporated with Hough Transform to solve semantic image segmentation problems. By placing it after a Hough Transform layer, "in
Externí odkaz:
http://arxiv.org/abs/2402.02946
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:
Bulatov, Konstantin, Emelianova, Ekaterina, Tropin, Daniil, Skoryukina, Natalya, Chernyshova, Yulia, Sheshkus, Alexander, Usilin, Sergey, Ming, Zuheng, Burie, Jean-Christophe, Luqman, Muhammad Muzzamil, Arlazarov, Vladimir V.
Publikováno v:
Computer Optics, volume 46, issue 2, p. 252-270, 2022
Identity documents recognition is an important sub-field of document analysis, which deals with tasks of robust document detection, type identification, text fields recognition, as well as identity fraud prevention and document authenticity validatio
Externí odkaz:
http://arxiv.org/abs/2107.00396
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
Publikováno v:
2020 25th International Conference on Pattern Recognition (ICPR), (2021) 9689-9695
This paper considers arbitrary document detection performed on a mobile device. The classical contour-based approach often fails in cases featuring occlusion, complex background, or blur. The region-based approach, which relies on the contrast betwee
Externí odkaz:
http://arxiv.org/abs/2008.02615
In this paper, we consider a task of stopping the video stream recognition process of a text field, in which each frame is recognized independently and the individual results are combined together. The video stream recognition stopping problem is an
Externí odkaz:
http://arxiv.org/abs/2008.02566
Publikováno v:
International Journal of Applied Engineering Research (ISSN 0973-4562), Volume 11, Number 24 (2016), pp. 11675-11680
In this paper we consider speedup potential of morphological image filtering on ARM processors. Morphological operations are widely used in image analysis and recognition and their speedup in some cases can significantly reduce overall execution time
Externí odkaz:
http://arxiv.org/abs/2002.09474
In this work the methods of comparison of digitized copies of administrative documents were considered. This problem arises, for example, when comparing two copies of documents signed by two parties in order to find possible modifications made by one
Externí odkaz:
http://arxiv.org/abs/2001.10785
The paper proposes an approach to training a convolutional neural network using information on the level of distortion of input data. The learning process is modified with an additional layer, which is subsequently deleted, so the architecture of the
Externí odkaz:
http://arxiv.org/abs/1912.00664