AI is great where statistical accuracy is more valuable.
This would be a good test to run competitive models over, one model is optimized to find the target tree with a 80+% confidence, the second model is optimized to find all trees which are not the target with the same confidence. Where the two models agree, run the first model again but with a confidence requirement of 99+% (which will take much longer to run) over the smaller data set.
So basically AI is good at categorizing data where perfect accuracy isn’t needed, but manual categorization isn’t feasible.
Kinda,
AI is great where statistical accuracy is more valuable.
This would be a good test to run competitive models over, one model is optimized to find the target tree with a 80+% confidence, the second model is optimized to find all trees which are not the target with the same confidence. Where the two models agree, run the first model again but with a confidence requirement of 99+% (which will take much longer to run) over the smaller data set.