Best way to perform categorization of multiple objects in one single picture

I have the following scenario. I succesfully trained an image classifier to identify black bears and grizzlies.
I do not have a training set of bears with bounding boxes.
Imagine that I have now a picture containing 2 grizzlies and 1 black bear. Is there a way to identify them, count them and idenitify their position? A naive way would be to split the image in sub-images and identify them on each sub-image, and then recompose the image.
I’ve seen this approach: but I am curious if there is a way to do that.

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In lesson 7 from last year there’s an example of Class Activation Maps (CAM). Here is a paper with more details and examples.

Hope this helps!

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