Classification of Aircraft in Remote Sensing Images Based on Deep Convolutional Neural Networks

Convolutional Neural Network (CNN) is a component of Deep Learning(DL) recently exploited in different fifields. In this work, we improve the performance of multi-label classifification based on CNN for remote sensing images of aircraft types. Intensive preprocessing limits the classifification rate...

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Bibliographic Details
Published inStatistics, optimization & information computing Vol. 10; no. 1; pp. 4 - 11
Main Authors BEN YOUSSEF, Youssef, Merrouchi, Mohamed, Abdelmounim, Elhassane, Gadi, Taoufiq
Format Journal Article
LanguageEnglish
Published 08.02.2022
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Summary:Convolutional Neural Network (CNN) is a component of Deep Learning(DL) recently exploited in different fifields. In this work, we improve the performance of multi-label classifification based on CNN for remote sensing images of aircraft types. Intensive preprocessing limits the classifification rate in previous studies. In order to avoid under-fifitting and over-fifitting problems, we optimized the architecture and Network parameters. To validate our method the recent public image dataset called Multi-Type Aircraft Remote Sensing Images (MTARSI) is used. Extensive experiments prove the effectiveness of the proposed method in terms of classifification rate.
ISSN:2311-004X
2310-5070
DOI:10.19139/soic-2310-5070-1143