Remote Sensing Scene Classification Using Convolutional Neural Network

Abstract

Several sectors can benefit from the use of remote sensing picture scene classification, which strives to classify remote sensing images into a number of semantic categories depending on their content. Deep learning-based remote sensing image scene categorization has generated a lot of attention and achieved significant strides as a result of these networks' strong feature learning skills. To the best of our knowledge, there hasn't been a comprehensive analysis of recent deep learning advances for scene classification in remote sensing images. This process provides a thorough evaluation of deep learning algorithms for remote sensing picture scene classification, which is crucial given the field's rapid progress. The remote sensing scene is analyzed using the deep learning algorithm from the input remote sensing photographs, and then the deep learning method is utilized. After all of the images have been trained, the deep learning technique predicts the outcome using accuracy, precision, recall, and F1-score.