Open AccessApplication of convolutional neural networks in optical text recognition to junk data filtering
Author(s) -
T E Razumov,
Д. В. Чуриков,
O. V. Kravchenko
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 - 10.1088/1742-6596/2127/1/012024
Subject(s) - computer science , convolutional neural network , classifier (uml) , artificial intelligence , software , artificial neural network , architecture , machine learning , pattern recognition (psychology) , data mining , information retrieval , operating system , art , visual arts
In this paper, the problem of constructing a model for detecting and filtering unwanted spam messages is solved. A fully connected convolutional neural network (FCNN) was chosen as the model of the classifier of unwanted emails in email. It allows you to divide emails into two categories: spam and not spam . The main result of the research is a software application in the C++ language, which has a micro-service architecture and solves the problem of image classification. The app can handle more than 10 6 requests per minute in real-time.