Neural Network Training System for Marker Encoding


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详细

In this paper, we propose a training system for visual markers that provides the generation and subsequent recognition (under real-world conditions) of stylized images that contain information encoded by a sequence of bits. New types of neural network layers that make the recognition process tolerant to external noise are developed. The training process is based on the end-to-end principle, which enables automatic training for the intermediate stages of the model. The experimental results that demonstrate the performance of the system in encoding and decoding artificial markers are presented.

作者简介

L. Wang

Nanjing University of Aeronautics and Astronautics

Email: tsurkov@ccas.ru
中国, Nanjing

O. Grinchuk

Moscow Institute of Physics and Technology

编辑信件的主要联系方式.
Email: oleg.grinchuk@phystehc.edu
俄罗斯联邦, Dolgoprudny, 141701

V. Tsurkov

Moscow Institute of Physics and Technology; Federal Research Center Computer Science and Control, Russian Academy of Sciences

编辑信件的主要联系方式.
Email: tsurkov@ccas.ru
俄罗斯联邦, Dolgoprudny, 141701; Moscow, 119991


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