  Simi-Supervised Recognition Challenge-FGVC7 is a challenging fine-grained
recognition competition. One of the difficulties of this competition is how to
use unlabeled data. We adopted pseudo-tag data mining to increase the amount of
training data. The other one is how to identify similar birds with a very small
difference, especially those have a relatively tiny main-body in examples. We
combined generic image recognition and fine-grained image recognition method to
solve the problem. All generic image recognition models were training using
PaddleClas . Using the combination of two different ways of deep recognition
models, we finally won the third place in the competition.
