INFORMATION CHANGE THE WORLD

International Journal of Engineering and Manufacturing(IJEM)

ISSN: 2305-3631 (Print), ISSN: 2306-5982 (Online)

Published By: MECS Press

IJEM Vol.8, No.4, Jul. 2018

Remote Sensing Image Scene Classification

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Author(s)

Md. Arafat Hussain, Emon Kumar Dey

Index Terms

Convolutional Neural Network;Remote Sensing Image;Scene Classification;CNN

Abstract

Remote sensing image scene classification has gained remarkable attention because of its versatile use in different applications like geospatial object detection, natural hazards detection, geographic image retrieval, environment monitoring and etc. We have used the strength of convolutional neural network in scene image classification and proposed a new CNN to classify the images. Pre-trained VGG16 and ResNet50 are used to reduce overfitting and the training time in this paper. We have experimented on a recently proposed NWPU-RESISC45 dataset which is the largest dataset of remote sensing scene images. This paper found a significant improvement of accuracy by applying the proposed CNN and also the approaches have applied.

Cite This Paper

Md. Arafat Hussain, Emon Kumar Dey,"Remote Sensing Image Scene Classification", International Journal of Engineering and Manufacturing(IJEM), Vol.8, No.4, pp.13-20, 2018.DOI: 10.5815/ijem.2018.04.02

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