Search Results for author: Elena Limonova

Found 7 papers, 1 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.

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 Implementation of Morphological Filtering Using ARM NEON Extension

no code implementations19 Feb 2020 Elena Limonova, Arseny Terekhin, Dmitry Nikolaev, Vladimir Arlazarov

Experiments showed 3 times efficiency increase for final implementation of erosion and dilation compared to van Herk/Gil-Werman algorithm without SIMD, 5. 7 times speedup for 8x8 matrix transpose and 12 times speedup for 16x16 matrix transpose compared to transpose without SIMD.

Computational optimization of convolutional neural networks using separated filters architecture

no code implementations18 Feb 2020 Elena Limonova, Alexander Sheshkus, Dmitry Nikolaev

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

The Analysis of Projective Transformation Algorithms for Image Recognition on Mobile Devices

no code implementations3 Dec 2019 Anton Trusov, Elena Limonova

In this work we apply commonly known methods of non-adaptive interpolation (nearest pixel, bilinear, B-spline, bicubic, Hermite spline) and sampling (point sampling, supersampling, mip-map pre-filtering, rip-map pre-filtering and FAST) to the problem of projective image transformation.

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.

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