The target recognition accuracy of remote sensing images is not satisfied. The labels of images acquisition and
recollecting are difficult and expensive. In order to solve the problem, we introduce transfer learning into Network
Boosting algorithm (NB) and propose Transfer Network Learning algorithm (TNL), in which other out-date data are
reused to instruct the remote sensing target recognition. TNL is suitable to improve the performance of remote sensing
target recognition, in which instances transfer learning is adopted for domain adaptation. The experimental results on the
MSTAR SAR data set and remote sensing data set including two-class planes show that the proposed algorithm has
better performance and achieves different domains learning.