What is the false alarm rate of AI Detector?
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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)