Applying Generative Adversarial Networks to Intelligent Subsurface Imaging and Identification

no code implementations • 30 May 2019 • William Rice

The numerical experiment illustrated that, based on the augmented training data, the proposed GAN architecture demonstrated a significant increase (from 82% to 98%) in the accuracy of the object classifier.

General Classification GPR +1