"De-SaTE: Denoising Self-attention Transformer Encoders for Li-ion Battery ..."

Gaurav Shinde et al. (2023)

> Home

Details and statistics

DOI: 10.1109/BIGDATA59044.2023.10386134

access: closed

type: Conference or Workshop Paper

metadata version: 2024-02-02

- view
  - electronic edition via DOI
  - unpaywalled version
  authority control:
- export record
  dblp key:
  - conf/bigdataconf/ShindeMKS23
- ask others
- share record
  persistent URL:
  - https://dblp.org/rec/conf/bigdataconf/ShindeMKS23
Gaurav Shinde, Rohan Mohapatra, Pooja Krishan, Saptarshi Sengupta:
De-SaTE: Denoising Self-attention Transformer Encoders for Li-ion Battery Health Prognostics. IEEE Big Data 2023: 2221-2228

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.