Radiation source working mode identification method based on transfer learning

The invention discloses a radiation source working mode identification method based on transfer learning, which comprises the following steps: acquiring small sample radiation source data, and selecting auxiliary data from the existing radiation source working mode data; forming a source domain of transfer learning by the small sample radiation source data and the selected auxiliary data; taking the radiation source data to be identified as a target domain of transfer learning; manifold feature learning is carried out on samples of the source domain and the target domain; obtaining an overall distribution difference between the source domain after manifold feature learning and the target domain after manifold feature learning, and obtaining training data; and optimizing the classifier based on the training data, and obtaining a radiation source working mode of the target domain. The method solves the problem that a small sample is difficult to identify the working mode of the radiation source. 本发明公开了供一种基于迁移学习