title: ÐÐ¿Ð¿Ð°ÑÐ°ÑÐ½Ð°Ñ ÑÐµÐ°Ð»Ð¸Ð·Ð°ÑÐ¸Ñ ÑÐ²ÐµÑÑÐ¾ÑÐ½Ð¾Ð¹ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð¾Ð¹ ÑÐµÑÐ¸ Ð´Ð»Ñ ÑÐ¸ÑÑÐµÐ¼Ñ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð±Ð°ÐºÐ°Ð»Ð°Ð²ÑÐ°
titleType: Subtitle
title: The hardware implementation of a convoluted neural network for the recognition system.
Creators: name: ÐÐºÐ¸Ð¼Ð¾Ð²Ð°, Ð®Ð»Ð¸Ñ
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2023
Subjects: Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð°Ñ ÑÐµÑÑ
ÑÐ²ÐµÑÑÐ¾ÑÐ½Ð°Ñ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½Ð°Ñ ÑÐµÑÑ
Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ð¸ÑÑÐµÐ¼Ð°Ñ Ð»Ð¾Ð³Ð¸ÑÐµÑÐºÐ°Ñ Ð¸Ð½ÑÐµÐ³ÑÐ°Ð»ÑÐ½Ð°Ñ ÑÑ ÐµÐ¼Ð°
ÑÐ·ÑÐº Ð¾Ð¿Ð¸ÑÐ°Ð½Ð¸Ñ Ð°Ð¿Ð¿Ð°ÑÐ°ÑÑÑÑ
Verilog
neural network
convolutional neural network
field-programmable gate array
hardware description language

description: Ð ÑÐ¾Ð´Ðµ ÑÐ°Ð±Ð¾ÑÑ ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ñ Ð°Ð»Ð³Ð¾ÑÐ¸ÑÐ¼Ñ Ð¸ ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ½ÑÐµ Ð¿ÑÐ¾Ð³ÑÐ°Ð¼Ð¼Ñ Ð´Ð»Ñ ÑÐ°ÑÐ¿Ð¾Ð·Ð½Ð°Ð²Ð°Ð½Ð¸Ñ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ð¹ Ð½Ð° Ð°Ð¿Ð¿Ð°ÑÐ°ÑÐ½Ð¾Ð¼ ÑÑÐ¾Ð²Ð½Ðµ Ñ Ð¸ÑÐ¿Ð¾Ð»ÑÐ·Ð¾Ð²Ð°Ð½Ð¸ÐµÐ¼ Ð¼ÐµÑÐ¾Ð´Ð° Ð¼Ð¾Ð´ÐµÐ»ÑÐ½Ð¾-Ð¾ÑÐ¸ÐµÐ½ÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð½Ð¾Ð³Ð¾ Ð¿ÑÐ¾ÐµÐºÑÐ¸ÑÐ¾Ð²Ð°Ð½Ð¸Ñ. ÐÐ°Ð´Ð°ÑÐ¸, ÐºÐ¾ÑÐ¾ÑÑÐµ Ð±ÑÐ»Ð¸ ÑÐµÑÐµÐ½Ñ Ð² ÑÐ¾Ð´Ðµ Ð¸ÑÑÐ»ÐµÐ´Ð¾Ð²Ð°Ð½Ð¸Ñ: 1) ÐÑÐ»Ð° Ð¿ÑÐµÐ´Ð¿ÑÐ¸Ð½ÑÑÐ° Ð¿Ð¾Ð¿ÑÑÐºÐ° ÑÐ¾Ð·Ð´Ð°Ð½Ð¸Ñ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐ¸ Ð½Ð° ÑÐ·ÑÐºÐµ Matlab Ñ ÑÐ¾ÑÐ½Ð¾ÑÑÑÑ Ð¿ÑÐµÐ´ÑÐºÐ°Ð·Ð°Ð½Ð¸Ñ 99,08%. 2) ÐÑÐ»Ð° ÑÐ°Ð·ÑÐ°Ð±Ð¾ÑÐ°Ð½Ð° Ð¼Ð¾Ð´ÐµÐ»Ñ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐ¸ Ð½Ð° ÑÐ·ÑÐºÐµ Python, ÑÐ¾Ð´ÐµÑÐ¶Ð°ÑÐ°Ñ 7 ÑÐ»Ð¾ÐµÐ² Ñ ÑÐ¾ÑÐ½Ð¾ÑÑÑÑ Ð¿ÑÐµÐ´ÑÐºÐ°Ð·Ð°Ð½Ð¸Ñ Ð² 99,54%. 3) ÐÐ¾Ð´ÐµÐ»Ñ Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐ¸ Ð±ÑÐ»Ð° Ð¾Ð¿ÑÐ¸Ð¼Ð¸Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð° Ð¿ÑÑÐµÐ¼ ÑÐ¼ÐµÐ½ÑÑÐµÐ½Ð¸Ñ ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²Ð° ÑÐ¸Ð»ÑÑÑÐ¾Ð² Ð² ÑÐ»Ð¾ÑÑ Ð¸ Ð¸Ð·Ð¼ÐµÐ½ÐµÐ½Ð¸ÐµÐ¼ ÑÐ°Ð·Ð¼ÐµÑÐ° ÑÐ´ÑÐ°, ÑÐ¾ÑÐ½Ð¾ÑÑÑ Ð¿ÑÐµÐ´ÑÐºÐ°Ð·Ð°Ð½Ð¸Ñ ÑÐ½Ð¸Ð·Ð¸Ð»Ð°ÑÑ Ð´Ð¾ 86,96%. 4) ÐÐ¾Ð»ÑÑÐµÐ½Ð½ÑÐµ Ð²ÐµÑÐ°, ÑÐµÑÑÐ¾Ð²ÑÐµ Ð¸Ð·Ð¾Ð±ÑÐ°Ð¶ÐµÐ½Ð¸Ñ, Ð° ÑÐ°Ðº Ð¶Ðµ Ð°ÑÑÐ¸ÑÐµÐºÑÑÑÐ° Ð½ÐµÐ¹ÑÐ¾ÑÐµÑÐ¸ Ð±ÑÐ»Ð¸ ÐºÐ¾Ð½Ð²ÐµÑÑÐ¸ÑÐ¾Ð²Ð°Ð½Ñ Ð² ÑÐ¾ÑÐ¼Ð°Ñ, ÑÐ¾Ð²Ð¼ÐµÑÑÐ¸Ð¼ÑÐ¹ Ñ ÐÐÐÐ¡. 5) ÐÑÐ» Ð¿ÑÐ¾Ð²ÐµÐ´ÐµÐ½ Ð»Ð¾Ð³Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ¸Ð½ÑÐµÐ· Ð¿Ð¾Ð»ÑÑÐµÐ½Ð½Ð¾Ð³Ð¾ HDL-ÐºÐ¾Ð´Ð°, ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ ÐºÐ¾ÑÐ¾ÑÐ¾Ð³Ð¾ ÑÐ¾Ð²Ð¿Ð°Ð»Ð¸ Ñ ÑÐµÐ¾ÑÐµÑÐ¸ÑÐµÑÐºÐ¸Ð¼Ð¸ Ð¿ÑÐµÐ´Ð¿Ð¾Ð»Ð¾Ð¶ÐµÐ½Ð¸ÑÐ¼Ð¸. ÐÐ¾Ð»ÑÑÐµÐ½Ð½ÑÐµ ÑÐµÐ·ÑÐ»ÑÑÐ°ÑÑ Ð¸Ð¼ÐµÑÑ Ð±Ð¾Ð»ÑÑÐ¾Ðµ Ð¿ÑÐ°ÐºÑÐ¸ÑÐµÑÐºÐ¾Ðµ Ð·Ð½Ð°ÑÐµÐ½Ð¸Ðµ Ð²Ð¾ Ð¼Ð½Ð¾Ð³Ð¸Ñ ÑÑÐµÑÐ°Ñ Ð´ÐµÑÑÐµÐ»ÑÐ½Ð¾ÑÑÐ¸, Ð²ÐºÐ»ÑÑÐ°Ñ Ð¼ÐµÐ´Ð¸ÑÐ¸Ð½Ñ, Ð°Ð²ÑÐ¾Ð¼Ð°ÑÐ¸ÑÐµÑÐºÐ¾Ðµ Ð²Ð¾Ð¶Ð´ÐµÐ½Ð¸Ðµ, ÑÐ¾Ð±Ð¾ÑÐ¾ÑÐµÑÐ½Ð¸ÐºÑ, ÐºÐ¾Ð½ÑÑÐ¾Ð»Ñ ÐºÐ°ÑÐµÑÑÐ²Ð° Ð¸ Ð¿ÑÐµÐ´ÑÑÐ°Ð²Ð»ÑÑÑ Ð±Ð¾Ð»ÑÑÐ¾Ð¹ Ð½Ð°ÑÑÐ½ÑÐ¹ Ð¸Ð½ÑÐµÑÐµÑ Ð² Ð¾Ð±Ð»Ð°ÑÑÐ¸ ÐºÐ¾Ð¼Ð¿ÑÑÑÐµÑÐ½Ð¾Ð³Ð¾ Ð·ÑÐµÐ½Ð¸Ñ.
description: The aim of this work is the hardware implementation of a convolutional neural network for image recognition systems. During the research, algorithms and computer programs for image recognition at the hardware level were developed using the model-driven design approach. The following tasks were accomplished during the study: 1) An attempt was made to create a neural network using Matlab with a prediction accuracy of 99.08%. 2) A neural network model was developed using Python language, consisting of 7 layers with a prediction accuracy of 99.54%. 3) The neural network model was optimized by reducing the number of filters in the layers and changing the kernel size, resulting in a decreased prediction accuracy of 86.96%. 4) The obtained weights, test images, and the architecture of the neural network were converted to a format compatible with FPGA. 5) Logical synthesis of the generated HDL code was performed, and the results matched the theoretical assumptions. The obtained results have significant practical value in various fields of activity, including medicine, autonomous driving, robotics, quality control, and represent significant scientific interest in the field of machine vision.