Deep supervised learning has achieved great success in the last decade. However, its defects of heavy dependence on manual labels and vulnerability to attacks have driven people to find other ...

To alleviate these problems, this article develops a physics-informed self-supervised neural network (SSN) to attenuate internal multiples by reducing requirements for prior information and employing ...