"Noise tolerant ternary weight deep neural networks for analog in-memory ..."

Jonas Doevenspeck et al. (2021)

> Home

Details and statistics

DOI: 10.1109/IJCNN52387.2021.9533684

access: closed

type: Conference or Workshop Paper

metadata version: 2021-09-29

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/ijcnn/DoevenspeckVLMD21
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/ijcnn/DoevenspeckVLMD21
Jonas Doevenspeck, Peter Vrancx, Nathan Laubeuf, Arindam Mallik, Peter Debacker, Diederik Verkest, Rudy Lauwereins, Wim Dehaene:
Noise tolerant ternary weight deep neural networks for analog in-memory inference. IJCNN 2021: 1-8

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.