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I think it’s worth reading the original assignment:

https://dspace.mit.edu/bitstream/handle/1721.1/6125/AIM-100....

If you want to argue that “likely objects” is weaker than Munroe intended, I think that’s a valid position but also that we’re certainly overthinking it.



It's specific-object identification, not object categorization. Also in front of a controlled background. They had a limited set of known objects. There was no generalization expected. It asked if it's looking at one specific ball or one specific hammer, not the general category of bird in the wild.

In fact, that scope was solved fairly fast, using techniques like Canny edge detection and Minkowski fractal dimension features, Hu moment features on Otsu thresholding etc.


I respectfully submit that this might be expecting too much precision from the alt text of a webcomic, xkcd.


The story is told basically in every single course on computer vision around the beginning.


I have higher standards for college courses. You have my blessing to criticize them for insufficient precision.




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