How can I develop an object detection system that counts the number of objects and determines their position in an image?
Is it possible that the fine-tuned pre-trained model performs worse than the original pre-trained model?
How can I prevent the CNN from classifying a new input into one of the existing labels (it was trained with) when the input has a new different label?
If an image contains two distinct objects, should I create a copy of this image with distinct labels for each copy?
How does non-max suppression work when one or multiple bounding boxes are predicted for the same object?
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