Improved remote sensing image scene classification method based on MobileNetV2
In order to solve the problems of low accuracy and low precision of traditional methods in remote sensing image scene classification,a remote sensing image scene classification method based on transfer learning and attention mechanism was proposed.Firstly,the second-generation mobile network(MobileNetV2)was used as the base network model;secondly,transfer learning was introduced to prevent the model from overfitting;finally,the attention mechanism module was introduced to make the model focus on the key feature information in the image.Experiments were conducted on the aerial image dataset(AID)and remote sensing image scene dataset(NWPU45),and the accuracies reached 96.88%and 95.45%,respectively.Experimental results show that the proposed method in this paper can effectively improve the classification accuracy of remote sensing image scenes.
万方数据
维普
