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.
A survey on data compression techniques: From the perspective of data quality, coding schemes, data type and applications,
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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.