Structure of transferred MS-CNN for SAR target recognition. Firstly, raw SAR images and transformed SAR images is utilized in MS-CNN to extract information, and the extracted features are by normalization operation to preprocess the learned features. -en, the learned features are transformed to Max-Slice block; and the obtained feature maps are scaled to different size and operated with feature aggregation; meanwhile, the processed feature maps are merged and associated with each specified size. -irdly, various filters are utilized to obtain the feature information and max-pooling is served to enforce the robustness of the features. -e fully connected high-level feature layer and softmax layer predict the recognized classes. Finally, parameters from outside datasets are transferred to the target classification