Yintong Wang^1,2,*, Yingjie Yang², Haiyan Chen³, Hao Zheng¹, Heyou Chang¹

Intelligent Automation & Soft Computing, Vol.34, No.1, pp. 371-388, 2022, DOI:10.32604/iasc.2022.027146

Abstract Handwritten Chinese recognition which involves variant writing style, thousands of character categories and monotonous data mark process is a long-term focus in the field of pattern recognition research. The existing methods are facing huge challenges including the complex structure of character/line-touching, the discriminate ability of similar characters and the labeling of training datasets. To deal with these challenges, an end-to-end residual attention handwritten Chinese paragraph text recognition method is proposed, which uses fully convolutional neural networks as the main structure of feature extraction and employs connectionist temporal classification as a loss function. The novel residual attention gate block is more… More >

Ying Fu^1,2,*, Minxue Gong¹, Guang Yang¹, Hong Wei³, Jiliu Zhou^1,2

CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 1359-1374, 2021, DOI:10.32604/cmc.2021.016536

Abstract Generative adversarial networks (GANs) have considerable potential to alleviate challenges linked to data scarcity. Recent research has demonstrated the good performance of this method for data augmentation because GANs synthesize semantically meaningful data from standard signal distribution. The goal of this study was to solve the overfitting problem that is caused by the training process of convolution networks with a small dataset. In this context, we propose a data augmentation method based on an evolutionary generative adversarial network for cardiac magnetic resonance images to extend the training data. In our structure of the evolutionary GAN, the most optimal generator is… More >

Chein-Shan Liu¹, Yung-Wei Chen², Jiang-Ren Chang²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.3, No.2, pp. 93-100, 2007, DOI:10.3970/icces.2007.003.093

Abstract A new collocation method is developed here to solve the elliptic boundary value problems with singularities. Specifically, we consider the Motz problem as a test of the performance of the new method, which is found accurate and effective. More >