A lightweight autoencoder with residual vector quantization and adversarial training compresses wind turbine pressure data by up to 10,240x with under 3% error, running on a low-power GAP9 MCU.
Tiny on-device structural health monitoring for wind turbines using mems pressure sensors,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
citation-role summary
background 1
citation-polarity summary
fields
cs.LG 1years
2025 1verdicts
CONDITIONAL 1roles
background 1polarities
unclear 1representative citing papers
citing papers explorer
-
EdgeCodec: Onboard Lightweight High Fidelity Neural Compressor with Residual Vector Quantization
A lightweight autoencoder with residual vector quantization and adversarial training compresses wind turbine pressure data by up to 10,240x with under 3% error, running on a low-power GAP9 MCU.