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20182021
most citedComputational optimization of convolutional neural networks using separated filters architecture

5 citations · 5 across the 2 of their papers we have counts for

collaborators

6 papers

cs.CV2021

Tiny CNN for feature point description for document analysis: approach and dataset

A. Sheshkus, A. Chirvonaya, V. L. Arlazarov

In this paper, we study the problem of feature points description in the context of document analysis and template matching. Our study shows that the specific training data is requ…

cs.CV20205 cited

Computational optimization of convolutional neural networks using separated filters architecture

Elena Limonova, Alexander Sheshkus, Dmitry Nikolaev

This paper considers a convolutional neural network transformation that reduces computation complexity and thus speedups neural network processing. Usage of convolutional neural ne…

cs.CV2020

Vanishing Point Detection with Direct and Transposed Fast Hough Transform inside the neural network

A. Sheshkus, A. Chirvonaya, D. Matveev +2

In this paper, we suggest a new neural network architecture for vanishing point detection in images. The key element is the use of the direct and transposed Fast Hough Transforms s…

cs.CV2019

Recognition of Images of Korean Characters Using Embedded Networks

Sergey A. Ilyuhin, Alexander V. Sheshkus, Vladimir L. Arlazarov

Despite the significant success in the field of text recognition, complex and unsolved problems still exist in this field. In recent years, the recognition accuracy of the English…

cs.CV2019

HoughNet: neural network architecture for vanishing points detection

Alexander Sheshkus, Anastasia Ingacheva, Vladimir Arlazarov +1

In this paper we introduce a novel neural network architecture based on Fast Hough Transform layer. The layer of this type allows our neural network to accumulate features from lin…

cs.CV2018

Optical Font Recognition in Smartphone-Captured Images, and its Applicability for ID Forgery Detection

Yulia S. Chernyshova, Mikhail A. Aliev, Ekaterina S. Gushchanskaia +1

In this paper, we consider the problem of detecting counterfeit identity documents in images captured with smartphones. As the number of documents contain special fonts, we study t…