Remote Sensing Image Classification using Deep Learning

Remote sensing is the technology used for extracting information about the earth surface with the help of sensors installed on the satellites. The remote sensing technology captures and analyzes the sensed data which also helps in planning and monitoring the use of regional data. In our work, we used deep learning to analyze remotely sensed data. This paper aims to identify buildings from the images and provide the result using one of the deep neural networks. Various models of Convolutional Neural Networks (CNNs) help in rapid and accurate analysis of remote sensing data. The significance of the work lies in training the model correctly without overfitting. The work achieves 72.97% accurate model.