"DOReN: Toward Efficient Deep Convolutional Neural Networks with Fully ..."

Souhail Meftah et al. (2021)

> Home

Details and statistics

DOI: 10.1109/TIFS.2021.3090959

access: closed

type: Journal Article

metadata version: 2023-08-28

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - journals/tifs/MeftahTMAVC21
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/journals/tifs/MeftahTMAVC21
Souhail Meftah, Benjamin Hong Meng Tan, Chan Fook Mun, Khin Mi Mi Aung, Bharadwaj Veeravalli, Vijay Chandrasekhar:
DOReN: Toward Efficient Deep Convolutional Neural Networks with Fully Homomorphic Encryption. IEEE Trans. Inf. Forensics Secur. 16: 3740-3752 (2021)

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.