These Tiny Bees Just Changed the Way We Think About AI Models

We chose models with Accuracy > 0.40 (and F1 score >0.35), seven in total (unshaded in Table 1) The regnet and mnasnet architectures demonstrated superior performance for our problem. We found a decline in day-to-day re-identification accuracy for all models, consistent with findings from \[16]. A similar trend was observed in retro-id for almost all of the models, as demonstrated by the sparkline graphs in Table 2.