The traditional ship detection algorithm is difficult to adapt in the complex and varied sea clutter environment, and intelligent ship detection is impossible to realize. This study proposes an improved region-based fully convolutional network (R-FCN) detection method. Aiming at the characteristics of synthetic aperture radar (SAR), the feature extraction network ResNet in R-FCN uses a mixed-scale convolution kernel. The feature extraction network can suppress the influence of the speckle noise and effectively extract the ship features. High-resolution GF-3 and low-resolution Sentinel-1 satellite SAR images are selected for the test. Consequently, good results are obtained, proving the effectiveness of the proposed algorithm.