Remote Sensing Image Scene Classification Meets Deep Learning: Challenges, Methods, Benchmarks, and Opportunities

by   Gong Cheng, et al.

Remote sensing image scene classification, which aims at labeling remote sensing images with a set of semantic categories based on their contents, has broad applications in a range of fields. Propelled by the powerful feature learning capabilities of deep neural networks, remote sensing image scene classification driven by deep learning has drawn remarkable attention and achieved significant breakthroughs. However, to the best of our knowledge, a comprehensive review of recent achievements regarding deep learning for scene classification of remote sensing images is still lacking. Considering the rapid evolution of this field, this paper provides a systematic survey of deep learning methods for remote sensing image scene classification by covering more than 140 papers. To be specific, we discuss the main challenges of scene classification and survey (1) Autoencoder-based scene classification methods, (2) Convolutional Neural Network-based scene classification methods, and (3) Generative Adversarial Network-based scene classification methods. In addition, we introduce the benchmarks used for scene classification and summarize the performance of more than two dozens of representative algorithms on three commonly-used benchmark data sets. Finally, we discuss the promising opportunities for further research.


page 1

page 3

page 6

page 7

page 10

page 11

page 12

page 20


Remote Sensing Image Scene Classification: Benchmark and State of the Art

Remote sensing image scene classification plays an important role in a w...

Convolution Neural Network Architecture Learning for Remote Sensing Scene Classification

Remote sensing image scene classification is a fundamental but challengi...

Remote Sensing Image Classification using Transfer Learning and Attention Based Deep Neural Network

The task of remote sensing image scene classification (RSISC), which aim...

Pairwise Comparison Network for Remote Sensing Scene Classification

Remote sensing scene classification aims to assign a specific semantic l...

Weight Initialization Techniques for Deep Learning Algorithms in Remote Sensing: Recent Trends and Future Perspectives

During the last decade, several research works have focused on providing...

Coupling Model-Driven and Data-Driven Methods for Remote Sensing Image Restoration and Fusion

In the fields of image restoration and image fusion, model-driven method...

Please sign up or login with your details

Forgot password? Click here to reset