Transfer learning of deep CNN de-noiser prior for Chinese ancient calligraphy tablet image denoising

Ge, Feihang; He, Lifeng; Chao, Yuyan

doi:10.1117/12.2550357

2019 International Conference on Image and Video Processing, and Artificial Intelligence 2019

DOI: 10.1117/12.2550357

|View full text |Cite

Transfer learning of deep CNN de-noiser prior for Chinese ancient calligraphy tablet image denoising

Feihang Ge¹,

Lifeng He²,

Yuyan Chao³

Help me understand this report

This publication either has no citations yet, or we are still processing them

Set email alert for when this publication receives citations?

See others like this or search for similar articles

scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

Contact Info

customersupport@researchsolutions.com

10624 S. Eastern Ave., Ste. A-614

Henderson, NV 89052, USA

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Blog Terms and Conditions API Terms Privacy Policy Contact Cookie Preferences Do Not Sell or Share My Personal Information

Made with 💙 for researchers

Part of the Research Solutions Family.

Transfer learning of deep CNN de-noiser prior for Chinese ancient calligraphy tablet image denoising

This publication either has no citations yet, or we are still processing them

See others like this or search for similar articles

Contact Info

Product

Resources

About