YOLO is known for its speed. However, it has been recently outperformed in terms of accuracy by Faster R-CNN (covered later in this chapter). Moreover, due to the way it detects objects, YOLO struggles with smaller objects. For instance, it would have trouble detecting single birds from a flock. As with most deep learning models, it also struggles to properly detect objects that deviate too much from the training set (unusual aspect ratios or appearance). Nevertheless, the architecture is constantly evolving, and those issues are being worked on.
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