Search Results for author: Vladimir V. Arlazarov

Found 12 papers, 5 papers with code

Fast matrix multiplication for binary and ternary CNNs on ARM CPU

no code implementations18 May 2022 Anton Trusov, Elena Limonova, Dmitry Nikolaev, Vladimir V. Arlazarov

In this paper, we propose novel fast algorithms of ternary, ternary-binary, and binary matrix multiplication for mobile devices with ARM architecture.

MIDV-2020: A Comprehensive Benchmark Dataset for Identity Document Analysis

no code implementations1 Jul 2021 Konstantin Bulatov, Ekaterina Emelianova, Daniil Tropin, Natalya Skoryukina, Yulia Chernyshova, Alexander Sheshkus, Sergey Usilin, Zuheng Ming, Jean-Christophe Burie, Muhammad Muzzamil Luqman, Vladimir V. Arlazarov

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 validation given photos, scans, or video frames of an identity document capture.

Face Detection

ResNet-like Architecture with Low Hardware Requirements

1 code implementation15 Sep 2020 Elena Limonova, Daniil Alfonso, Dmitry Nikolaev, Vladimir V. Arlazarov

In the paper, we introduce a bipolar morphological ResNet (BM-ResNet) model obtained from a much more complex ResNet architecture by converting its layers to bipolar morphological ones.

Edge-computing General Classification +1

Fast Implementation of 4-bit Convolutional Neural Networks for Mobile Devices

no code implementations14 Sep 2020 Anton Trusov, Elena Limonova, Dmitry Slugin, Dmitry Nikolaev, Vladimir V. Arlazarov

We introduce an efficient implementation of 4-bit matrix multiplication for quantized neural networks and perform time measurements on a mobile ARM processor.

Optical Character Recognition (OCR) Quantization

Fast Approximate Modelling of the Next Combination Result for Stopping the Text Recognition in a Video

1 code implementation6 Aug 2020 Konstantin Bulatov, Nadezhda Fedotova, Vladimir V. Arlazarov

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.

Video Recognition

Comparison of scanned administrative document images

no code implementations29 Jan 2020 Elena Andreeva, Vladimir V. Arlazarov, Oleg Slavin, Aleksey Mishev

In this work the methods of comparison of digitized copies of administrative documents were considered.

Training the Convolutional Neural Network with Statistical Dependence of the Response on the Input Data Distortion

no code implementations2 Dec 2019 Igor Janiszewski, Dmitry Slugin, Vladimir V. Arlazarov

The paper proposes an approach to training a convolutional neural network using information on the level of distortion of input data.

Bipolar Morphological Neural Networks: Convolution Without Multiplication

no code implementations5 Nov 2019 Elena Limonova, Daniil Matveev, Dmitry Nikolaev, Vladimir V. Arlazarov

To demonstrate efficiency of the proposed model we consider classical convolutional neural networks and convert the pre-trained convolutional layers to the bipolar morphological layers.

Next integrated result modelling for stopping the text field recognition process in a video using a result model with per-character alternatives

1 code implementation9 Oct 2019 Konstantin Bulatov, Boris Savelyev, Vladimir V. Arlazarov

This paper is directed on extending the stopping method based on next integrated recognition result modelling, in order for it to be used within a string result recognition model with per-character alternatives.

Object Recognition

MIDV-2019: Challenges of the modern mobile-based document OCR

1 code implementation9 Oct 2019 Konstantin Bulatov, Daniil Matalov, Vladimir V. Arlazarov

The portfolio of methods and algorithms for solving such tasks as face detection, document detection and rectification, text field recognition, and other, is growing, and the scarcity of datasets has become an important issue.

Face Detection Optical Character Recognition (OCR)

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