Design of neuron-calculators for the normalized equivalence of two matrix arrays based on FPGA for self-learning equivalently convolutional neural networks (SLE

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Design of neuron-calculators for the normalized equivalence of two matrix arrays based on FPGA for self-learning equivalently convolutional neural networks (SLE_CNNs)

Published:2019-05-14 Issue: Volume: Page:
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Container-title:Real-Time Image Processing and Deep Learning 2019
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Author:

Krasilenko Vladimir G.,Lazarev Alexander,Nikitovich Diana

Publisher

SPIE

Reference39 articles.

1. Recognition algorithms of multilevel images of multicharacter identification objects based on nonlinear equivalent metrics and analysis of experimental data;Krasilenko,2002

2. Recognition Algorithms of Images of Multi-Character Identification Objects Based jn Nonlinear Equivalent Metrics and Analysis of Experimental Dat Using Designed Software;Krasilenko,2012

3. Modelling and comparative analysis of correlation and mutual alignment equivalent images;Krasilenko,2009

4. Multiport optical associative memory based on matrix-matrix equivalentors;Krasilenko,1997

5. Research and design of equivalence model of heteroasociative memory;Krasilenko;The Scientific session of MIFI-2010,2010

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