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

Semi-Supervised Recognition under a Noisy and Fine-grained Dataset