Generative adversarial networks as a novel approach for tectonic fault and fracture extraction in high-resolution satellite and airborne optical images

HIGHLIGHTS

• who: XXIV ISPRS Congress ( and collaborators from the (UNIVERSITY) have published the research: GENERATIVE ADVERSARIAL NETWORKS AS A NOVEL APPROACH FOR TECTONIC FAULT AND FRACTURE EXTRACTION IN HIGH-RESOLUTION SATELLITE AND AIRBORNE OPTICAL IMAGES, in the Journal: (JOURNAL)
• what: The authors develop a novel method based on Deep Convolutional Networks (DCN) to automate the identification and mapping of fracture and fault traces in optical images. The authors propose a new loss function for both the Generator and the Discriminator networks to improve their accuracy. Using two criteria and a manually annotated optical image the authors . . .
  

   

  

  If you want to have access to all the content you need to log in!

  Thanks :)

  Username or Email

  Password

  Remember me

  Lost your password?

  If you don't have an account, you can create one here.