JOURNAL ARTICLE

Remote Sensing Image Scene Classification

Md. Arafat HussainEmon Kumar Dey

Year: 2018 Journal:   International Journal of Engineering and Manufacturing Vol: 8 (4)Pages: 13-20

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.

Keywords:
Convolutional neural network Overfitting Computer science Artificial intelligence Contextual image classification Remote sensing Geospatial analysis Image (mathematics) Object detection Computer vision Pattern recognition (psychology) Artificial neural network Geography

Metrics

11
Cited By
1.32
FWCI (Field Weighted Citation Impact)
23
Refs
0.84
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Remote-Sensing Image Classification
Physical Sciences →  Engineering →  Media Technology
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Remote Sensing and Land Use
Physical Sciences →  Earth and Planetary Sciences →  Atmospheric Science

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