Classification of Microwave Planar Filters by Deep Learning

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F22%3APU144685" target="_blank" >RIV/00216305:26220/22:PU144685 - isvavai.cz</a>

Result on the web

<a href="https://www.radioeng.cz/fulltexts/2022/22_01_0069_0076.pdf" target="_blank" >https://www.radioeng.cz/fulltexts/2022/22_01_0069_0076.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.13164/re.2022.0069" target="_blank" >10.13164/re.2022.0069</a>

Result language

angličtina

Original language name

Classification of Microwave Planar Filters by Deep Learning

Original language description

Over the last few decades, deep learning has been considered to be powerful tool in the classification tasks, and has become popular in many applications due to its capabil-ity of processing huge amount of data. This paper presents approaches for image recognition. We have applied convolu-tional neural networks on microwave planar filters. The first task was filter topology classification, the second task was filter order estimation. For the task a dataset was generated. As presented in the results, the created and trained neural networks are very capable of solving the selected tasks.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

20201 - Electrical and electronic engineering

Project

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Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2022

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Radioengineering

ISSN

1221-2512

e-ISSN

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Volume of the periodical

31

Issue of the periodical within the volume

1

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

8

Pages from-to

69-76

UT code for WoS article

000790989000009

EID of the result in the Scopus database

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