Attention-Based Convolutional Neural Network for the Detection of Built-Up Areas in High-Resolution SAR Images

The detection of built-up areas is essential for high-resolution Synthetic Aperture Rader (SAR) applications, such as urban planning and environmental monitoring. In this paper, we proposed an attention based convolutional neural network for the detection of built-up areas in SAR images. Our network composes of two parts. First part contains two branches, one is designed to obtain high detection rate and the other one is designed to obtain low false alarm rate. Second part aims to merge the advantages of the two detection results of first part by using attention mechanism. Experiments on TerraSAR-X high resolution SAR images over Beijing demonstrate the effectiveness of proposed method.