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 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.