Fig. 1.

The flowchart of our method. The model whose edge is imaginary line represents that its parameters are fixed. In Stage 1, an encoder $f_{\varphi }$ and a classifier g are initially trained using data in source domain (Section 2.1). In Stage 2, a discriminator $\mathcal{D}$ is trained to identify the domain of each subtomogram (Section 2.2). In Stage 3, labeled data in both domains are used to fine-tune the encoder $f_{\varphi }$ with the assistance of discriminator $\mathcal{D}$ (Section 2.3)