An Improved Self-Training Model with Fine-Tuning Teacher/Student Exchange Strategy to Detect Computer-Generated Images

Algorithm 1

Improved self-training algorithm with FTTSE.

	Input: labeled dataset & unlabeled dataset
	Output: model
(1)	Train teacher model with labeled dataset .
(2)	Use the trained teacher model to predict the pseudo label on unlabeled dataset .
	And then combine the pseudo-labeled dataset and the labeled dataset together to generate a mixed dataset.
(3)	Apply malicious attacks to to get attacked mixed image dataset
(4)	Train the student model with the attacked mixed image dataset .
(5)
(6)	while neural network unfitting do
(7)	Last student model is regarded as the teacher model to predict pseudo label and generate a new attacked mixed dataset
(8)	Last teacher model trained from previous round of iteration: is fine-tuned and used for retraining student model with dataset .
(9)	Implement the learning rate decay strategy to reduce the learning rate value as follows:
(10)
(11)	end while