Publication:
Comparison of Combinations of Data Augmentation Methods and Transfer Learning Strategies in Image Classification Used in Convolution Deep Neural Networks

Дата
2021
Авторы
Korzhebin, T. A.
Egorov, A. D.
Journal Title
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Научные группы
Организационные подразделения
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Организационная единица
Институт интеллектуальных кибернетических систем
Цель ИИКС и стратегия развития - это подготовка кадров, способных противостоять современным угрозам и вызовам, обладающих знаниями и компетенциями в области кибернетики, информационной и финансовой безопасности для решения задач разработки базового программного обеспечения, повышения защищенности критически важных информационных систем и противодействия отмыванию денег, полученных преступным путем, и финансированию терроризма.
Выпуск журнала
Аннотация
© 2021 IEEE.Several studies have already made a comparison of either Data Augmentation methods or Transfer learning strategies in Convolution Deep Neural Networks for Image Classification; however, comparison of combinations of Data Augmentation methods and Transfer learning strategies remains to be accomplished. Combination of Data Augmentation methods with the highest-performing results and Transfer learning strategy with the highest-performing results does not achieve top-performing results in total as well. We make the comparison of four Data Augmentation methods, the comparison of four Transfer learning strategies, used on five different image classification models and the comparison of all combinations of them. We use small dataset consists of 40 images for training and finetuning and accuracy as metric. Our research shows that the performance results of a model with combinations of methods and strategies cannot be expected from simple comparisons of parts of this combination.
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Цитирование
Korzhebin, T. A. Comparison of Combinations of Data Augmentation Methods and Transfer Learning Strategies in Image Classification Used in Convolution Deep Neural Networks / Korzhebin, T.A., Egorov, A.D. // Proceedings of the 2021 IEEE Conference of Russian Young Researchers in Electrical and Electronic Engineering, ElConRus 2021. - 2021. - P. 479-482. - 10.1109/ElConRus51938.2021.9396724
URI
https://www.doi.org/10.1109/ElConRus51938.2021.9396724
 https://www.scopus.com/record/display.uri?eid=2-s2.0-85104763923&origin=resultslist
 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=Alerting&SrcApp=Alerting&DestApp=WOS_CPL&DestLinkType=FullRecord&UT=WOS:000669709800107
 https://openrepository.mephi.ru/handle/123456789/23994
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