Systems and methods for fine tuning image classification neural networks

A non-transitory machine-readable medium storing instructions which, when executed by processing circuitry of one or more computing machines, cause the processing circuity to perform operations comprising:

• receiving, from a vision device comprising one or more cameras, a probe image;
• generating, using a trained facial classification neural engine, one or more first labels for a person depicted in the probe image and a probability for at least one of the one or more first labels;
• determining that the probability is within a predefined low accuracy range;
• generating, using a supporting engine, a second label for the person depicted in the probe image, wherein the supporting engine operates independently of the trained facial classification neural engine;
• further training the facial classification neural engine based on the second label.

A method comprising:

• receiving, from a vision device comprising one or more cameras, a probe image;
• generating, using a trained facial classification neural engine, one or more first labels for a person depicted in the probe image and a probability for at least one of the one or more first labels;
• determining that the probability is within a predefined low accuracy range;
• generating, using a supporting engine, a second label for the person depicted in the probe image, wherein the supporting engine operates independently of the trained facial classification neural engine;
• further training the facial classification neural engine based on the second label.