I am using Faster RCNN with Inception V2 on custom dataset. My model is working fine with good detection accuracy. However, I am facing false positive problem when I pass an image to the model I get correct prediction but I am also getting some wrong bounding boxes with high confidence score. Is there any method which can be used as a post-processing to remove these extra detection?
I am using Faster RCNN with Inception V2 on custom dataset. My model is working fine with good detection accuracy. However, I am facing false positive problem when I pass an image to the model I get correct prediction but I am also getting some wrong bounding boxes with high confidence score. Is there any method which can be used as a post-processing to remove these extra detection?