Thermostatic valve (FOMO-AD 96x96) - dataset collected by Edge Impulse - FOMO-AD

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Input layer (27,648 features)

MobileNetV2 0.35

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By definition there should be as few as possible anomalies in the training dataset, and thus accuracy is not calculated during training. Run Model testing to learn more about the model performance.

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Model	Author
MobileNetV2 0.35 Officially supported Uses around 296.8K RAM and 575.2K ROM with default settings and optimizations. Supports both RGB and grayscale.	Edge Impulse
MobileNetV2 0.1 Officially supported Uses around 270.2K RAM and 212.3K ROM with default settings and optimizations. Supports both RGB and grayscale.	Edge Impulse

These users will be notified over email when this job finishes.

	Name
	Jenny Plunkett Edge Impulse staff
	Louis Moreau Edge Impulse staff

Anomaly detection settings

Training settings

Augmentation settings

Advanced training settings

Neural network architecture

Model

MobileNetV2 0.35
Officially supported

MobileNetV2 0.1
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Anomaly detection settings

Training settings

Augmentation settings

Advanced training settings

Neural network architecture

Model

Description

Last training performance (validation set)

Accuracy

Loss

Confusion matrix (validation set)

Feature explorer (full training set)

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