"A Simple yet Effective Unsupervised Adversarial Example Generation ..."

Rongkun Zhang et al. (2020)

> Home

Details and statistics

DOI: 10.1007/978-981-16-1877-2_8

access: closed

type: Conference or Workshop Paper

metadata version: 2021-11-29

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/nctcs/ZhangLZ0Z20
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/nctcs/ZhangLZ0Z20
Rongkun Zhang, Dan Liu, Wentao Zhao, Qiang Liu, Chengzhang Zhu:
A Simple yet Effective Unsupervised Adversarial Example Generation Framework for Vulnerability Assessment on Deep Learning. NCTCS 2020: 107-122

manage site settings

To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.