Open AccessTo the question of realization of machine vision technology based on FPGA-architectures
Author(s) -
K A Timakov
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2142/1/012022
Subject(s) - field programmable gate array , computer science , convolutional neural network , realization (probability) , artificial intelligence , segmentation , machine vision , field (mathematics) , popularity , computer vision , computer architecture , embedded system , psychology , social psychology , statistics , mathematics , pure mathematics
In the last few years, machine learning and machine vision technologies have started to gain more and more popularity. This industry occupies one of the leading positions in the field of information technology. The paper is devoted to the development of a machine vision algorithm based on new generations of FPGAs for recognizing handwritten Cyrillic characters in images and video streams, in particular. The article raises the issues of using FPGA as an image segmentation accelerator and organizing work with the video stream, choosing the most suitable FPGA platform, creating training samples of handwritten characters, and working with the convolutional neural network AlexNet.