What is the false alarm rate of AI Detector?

What is the false alarm rate of AI Detector?

The false alarm rate of AI Detector varies significantly due to differences in application scenarios and technologies. The following is a typical data comparison:
Industry standard scope
Traditional AI devices: generally between 1% and 5%. If the PCB detection requirement does not exceed 10%, if it actually exceeds 3%, it needs to be shut down for debugging.
In the medical field, the misdiagnosis rate of AI is about 2% -5%, with a high misjudgment rate for mental illnesses and complex chronic diseases.
Financial risk control: The bank's AI system has a high false alarm rate, but the specific values have not been disclosed, and data quality needs to be optimized to reduce it.
Case of Technological Breakthrough
Pyrotechnics detection: the domestic edge computing box adopts the multi spectral fusion technology, and the false alarm rate is as low as 0.76 ‰ (only 76 false alarms per million detections).
Low altitude security: Tencent Cloud's intelligent system adopts a multimodal perception network, with a false alarm rate of only 0.01%.
Key influencing factors
Data quality: Errors or incomplete data can directly increase the false positive rate.
Model complexity: Overfitting may lead to over sensitivity to normal fluctuations.
(Note: It is assumed that there are relevant video resources here, and actual adjustments need to be made based on the material library)