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MicroNet Medium INT8

Description

This is a fully quantized version (asymmetrical int8) of the MicroNet Medium model developed by Arm, from the MicroNets paper. It is trained on the 'slide rail' task from http://dcase.community/challenge2020/task-unsupervised-detection-of-anomalous-sounds.

License

Apache-2.0

Related Materials

Class Labels

The class labels associated with this model can be created by running the script get_class_labels.sh.

Network Information

Network Information Value
Framework TensorFlow Lite
SHA-1 Hash ed709fccb1d57393cbc88f36da38a4ab70f97b4a
Size (Bytes) 463792
Provenance https://arxiv.org/pdf/2010.11267.pdf
Paper https://arxiv.org/pdf/2010.11267.pdf

Performance

Platform Optimized
Cortex-A ✖️
Cortex-M ✔️
Mali GPU ✔️
Ethos U ✔️

Key

  • ✔️ - Will run on this platform.
  • ✖️ - Will not run on this platform.

Accuracy

Dataset: Dcase 2020 Task 2 Slide Rail

Metric Value
AUC 0.963

Optimizations

Optimization Value
Quantization INT8

Network Inputs

Input Node Name Shape Description
input (1, 32, 32, 1) Input is 64 steps of a Log Mel Spectrogram using 64 mels resized to 32x32.

Network Outputs

Output Node Name Shape Description
Identity (1, 8) Raw logits corresponding to different machine IDs being anomalous