Research on Handwritten Digit Generation Method Based on Adversarial Generative Networks
To address these challenges,a handwritten digit generation method based on improved adversarial generation networks(GANs)is proposed.By introducing the generator and discriminator of GANs,an innovative network architecture was designed,and a series of training strategies were adopted to solve the instability and pattern collapse problems in GANs training.Through experiments using the MNIST dataset,the results showed that the new model achieved an accuracy of over 98％.Compared with traditional neural network methods,handwritten digit recognition systems based on improved ad-versarial generative networks have significant performance improvements.
number recognitioncomputer visionneural networksadversarial generative net-work
万方数据
维普
