I am working in object detection with my own dataset.
The objects present in my dataset are very umbalanced, and I was wondering if it is possible to apply something as a weighted random sampler (I have already employed this for image classification) but for object detection.
In my images several structures are present.
Balancing a mutli-label dataset is a bit tricky, as a simple weighted sampling might even increase the imbalance, e.g. if the majority classes are often associated with the oversampled minority classes.
There are a few approaches, such as SCUMBLE, REMEDIAL, MLSOL, MLSMOTE etc.
I don’t know, what the current state of the art is, but I’m sure @rasbt would know.
Thankyou so much @ptrblck, I will check the approaches you have given me.
I’ll provide I new answer if I reach a solution!
Did you find a solution? Thanks.
Hi, could you please share the approach which worked for you?