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I have tried dfine and deim and found that although they have a high detection rate, their false detection rate is also absurdly high, especially when the same object has almost no ability to distinguish between different states and outputs both states. Although the detection rate is high, it is not what I want. How to adjust the balance between detection rate and false detection rate
The text was updated successfully, but these errors were encountered:
I'm also experiencing this problem with excessive false positives. May I ask if you have tried some solutions, such as making the perturbation not limited to the box neighborhood in the denoising perturbation. We want the model to learn more background class information.
I have tried dfine and deim and found that although they have a high detection rate, their false detection rate is also absurdly high, especially when the same object has almost no ability to distinguish between different states and outputs both states. Although the detection rate is high, it is not what I want. How to adjust the balance between detection rate and false detection rate
The text was updated successfully, but these errors were encountered: