activity
20192023
most citedThe Analysis of Projective Transformation Algorithms for Image Recognition on Mobile Devices

7 citations · 23 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CV2023★ 2 cited

Unfolder: Fast localization and image rectification of a document with a crease from folding in half

A. M. Ershov, D. V. Tropin, E. E. Limonova +2

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 di…

cs.LG2022★ 2 cited

Fast matrix multiplication for binary and ternary CNNs on ARM CPU

Anton Trusov, Elena Limonova, Dmitry Nikolaev +1

Low-bit quantized neural networks are of great interest in practical applications because they significantly reduce the consumption of both memory and computational resources. Bina…

cs.CV2020

ResNet-like Architecture with Low Hardware Requirements

Elena Limonova, Daniil Alfonso, Dmitry Nikolaev +1

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, enhancem…

cs.CV2020

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

Anton Trusov, Elena Limonova, Dmitry Slugin +2

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-t…

cs.DC2020★ 7 cited

Fast Implementation of Morphological Filtering Using ARM NEON Extension

Elena Limonova, Arseny Terekhin, Dmitry Nikolaev +1

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…

cs.CV2020★ 5 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…