Automated design of a convolutional neural network with multi-scale filters for cost-efficient seismic data classification

Abstract

The authors present an automated design approach to propose a new neural network architecture for seismic data analysis. The new architecture classifies multiple seismic reflection datasets at extremely low computational cost compared with conventional architectures for image classification.