CDLNet: Collaborative Dictionary Learning Network for Remote Sensing Image Scene Classification

In recent years, deep learning-based methods have been extensively utilized in remote sensing image scene classification and have achieved remarkable performance. The wide geographical coverage and resolution differences of scene images result in significant within-class diversity and between-class similarity, hindering the further improvement of classification accuracy. Attention-based methods automatically estimate the importance of local regions by learning weight assignments, which effectively enhance the feature extraction capability of the network. However, methods that solely rely on the network to automatically learn weight assignments may introduce biases in the attention calculations. By analyzing…

• NN
  National Natural Science Foundation of China

  Award: 62071204
• CP
  China Postdoctoral Science Foundation

  Award: 2021M691275
• NS
  Natural Science Foundation of Jiangsu Province

  Award: BK20201338