External Links

Cite Key

Statistics

  • References: 0
  • Cited by: 0
  • Reviews: 0
  • Bibliographies: 0

PDF

Researchr

Researchr is a web site for finding, collecting, sharing, and reviewing scientific publications, for researchers by researchers.

Sign up for an account to create a profile with publication list, tag and review your related work, and share bibliographies with your co-authors.

FuzzGAN: A Generation-Based Fuzzing Framework for Testing Deep Neural Networks

Ge Han, Zheng Li, Peng Tang, Chengyu Hu, Shanqing Guo. FuzzGAN: A Generation-Based Fuzzing Framework for Testing Deep Neural Networks. In 24th IEEE Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application, HPCC/DSS/SmartCity/DependSys 2022, Hainan, China, December 18-20, 2022. pages 1601-1608, IEEE, 2022. [doi]

Authors

Ge Han

This author has not been identified. Look up 'Ge Han' in Google

Zheng Li

This author has not been identified. It may be one of the following persons: Look up 'Zheng Li' in Google

Peng Tang

This author has not been identified. Look up 'Peng Tang' in Google

Chengyu Hu

This author has not been identified. Look up 'Chengyu Hu' in Google

Shanqing Guo

This author has not been identified. Look up 'Shanqing Guo' in Google
runs on