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Found 7 papers, 1 papers with code
Fast matrix multiplication for binary and ternary CNNs on ARM CPU
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
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.
Fast Implementation of 4-bit Convolutional Neural Networks for Mobile Devices
We introduce an efficient implementation of 4-bit matrix multiplication for quantized neural networks and perform time measurements on a mobile ARM processor.
Fast Implementation of Morphological Filtering Using ARM NEON Extension
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
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
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
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.
