[sangfroid_bio]

Depends on whether you are looking for effectiveness vs efficiency. YOLO et al. are optimised for general feature extraction. They are ridiculously good if you need to build something quickly. If you are looking for the most efficient way e.g. lowest processing power per image then use a network that is optimised for the particular feature you are trying to extract.

[sillysaurusx]

Highest accuracy. I was mainly wondering which model ML engineers reach for circa 2020 for classification tasks. Searching for classifiers brings up article after article presenting toy classifiers, but very little with a production focus.

[dontreact]

I've seen people get good results with Efficientnet, and it scales to be quite large. In general, I look at whatever the best state of the art is on imagenet, but then look for implementations that look easy to use among the top few.