Convolutional neural network for satellite image classification

Abstract

Multimedia applications and processing is an exciting topic, and it is a key of many applications of artificial intelligent like video summarization, image retrieval or image classification. A convolutional neural networks have been successfully applied on multimedia approaches and used to create a system able to handle the classification without any human’s interactions. In this paper, we produce effective methods for satellite image classification that are based on deep learning and using the convolutional neural network for features extraction by using AlexNet, VGG19, GoogLeNet and Resnet50 pretraining models. The Resnet50 model achieves a promising result than other models on three different dataset SAT4, SAT6 and UC Merced Land. The accuracy of classification of this model for UC Merced Land dataset is 98%, for SAT4 is 95.8%, and the result for SAT6 is 94.1%.