Author:
Chepkov A O,Klimachev V S,Korchagin A I,Vlasov A I
Abstract
Abstract
The paper discusses the features of solving a class of problems for pattern recognition using the STM-32 microcontroller. The problem of pattern recognition can be solved on neural networks of different architectures, the main attention is paid to the Hamming neural network model. The features of the implementation of the Hamming network based on the STM-32 microcontroller for the recognition of images entered via the touch screen are analyzed. It is experimentally shown that the network cannot always correctly process the input value and compare it with the reference value of the class for digital test images. This is due to the high degree of similarity of some images and the presence of noise. In conclusion, recommendations on the implementation of neural network algorithms for image processing on microcontrollers are given.
Subject
General Physics and Astronomy
Reference19 articles.
1. Analysis of machine learning methods to improve efficiency of big data processing in industry 4.0;Prudius;Journal of Physics: Conference Series,2019
2. Projected capacitive touch technology;Barrett;Information Display,2010
3. Graphene flexible touchscreen with integrated analog-digital converter;Terent’ev;Russian Microelectronics,2017
4. Electrochromic thin-film components for information representation systems;Shakhnov;IOP Conference series: materials science and Engineering,2016
5. Investigation of a capacitor array of a composite capacitive touch panel;Krivoshein;Russian Microelectronics,2018