Traditional approaches for remote sensing image segmentation are mature in certain respect, as the new spaceborne technology of continuous observation satellite video emerges, it arises a new demand for moving object detection from this new data source. In the field of computer vision, deep learning technique has achieved outstanding performance for general images. In the research, a deep learning based method is introduced and several modifications are made in the processing steps. Faster Convolutional Neural Network (Faster CNN) algorithm is selected as the basal pipeline and conditional random field is used to generate finer detail proposals. After enforced iterations, the computed extraction result of ships in remote sensing satellite video data is compared with original Faster CNN method which demonstrates an improved target detection output in different tests.