This work is licensed under the Creative Commons Attribution 4.0 International License.
Xiao, Y., Lei, W., Lu, L., Chang, X., & Chen, X. (2021). Cs-gan: cross-structure generative adversarial networks for chinese calligraphy translation. Knowledge-Based Systems(5), 107334.Search in Google Scholar
Marumoto, S. M. (2013). Ink diffusion simulation for 3d virtual calligraphy. Journal of Advanced Computatioanl Intelligence and Intelligent Informatics, 17(4a99).Search in Google Scholar
Dong, J., Miao, X. U., & Pan, Y. H. (2009). Statistic model-based simulation on calligraphy creation: statistic model-based simulation on calligraphy creation. Chinese Journal of Computers, 31(7), 1276-1282.Search in Google Scholar
Abbasi, M. A., Fareen, N., & Abbasi, A. A. (2020). Urdu nastaleeq nib calligraphy pattern recognition. Science Publishing Group(2).Search in Google Scholar
Kaoudja, Z., Kherfi, M. L., & Khaldi, B. (2021). A new computational method for arabic calligraphy style representation and classification. Applied Sciences, 11(11), 4852.Search in Google Scholar
Wada, A., & Shin, J. (2012). Three dimensional virtual calligraphy simulation with pen tablet. International Journal of Engineering and Industries, 3(3), 31-42.Search in Google Scholar
Dai, Y. (2021). Research on the application of computer multimedia in calligraphy education. Journal of Physics Conference Series, 1915(3), 032019.Search in Google Scholar
Yuyin, W., & Yuhang, C. (2021). Influence of virtual imaging technology based on html5 technology on digital painting. Microprocessors and Microsystems, 82(9), 103855.Search in Google Scholar
Wu, S. J., Yang, C. Y., & Hsu, Y. J. (2020). Calligan: style and structure-aware chinese calligraphy character generator.Search in Google Scholar
Pervez, A., Ali, O., & Lee, D. (2016). Robotic Calligraphy: Learning From Character Images.Search in Google Scholar
A, G. L., A, Z. G., B, F. C. A., C, L. Y., B, X. C., & D, C. M. L., et al. (2021). Automatic stroke generation for style-oriented robotic chinese calligraphy. Future Generation Computer Systems.Search in Google Scholar
Gao, X., Zhou, C., Chao, F., Yang, L., & Shen, Q. (2019). A data-driven robotic chinese calligraphy system using convolutional auto-encoder and differential evolution. Knowledge-Based Systems, 182.Search in Google Scholar
Wu, R., Zhou, C., Chao, F., Yang, L., & Shang, C. (2019). Ganccrobot: generative adversarial nets based chinese calligraphy robot. Information Sciences, 516.Search in Google Scholar
Chao, F., Lin, G., Zheng, L., Chang, X., Lin, C. M., & Yang, L., et al. (2020). An lstm based generative adversarial architecture for robotic calligraphy learning system. Sustainability, 12.Search in Google Scholar
Chen, J., Yi, Y., & Song, B. (2020). Electromechanical model of coupling spring piezoelectric oscillator with loading. Mathematical Problems in Engineering, 2020.Search in Google Scholar