Chinese Journal of Intelligent Science and Technology ›› 2019, Vol. 1 ›› Issue (4): 415-420.doi: 10.11959/j.issn.2096-6652.201946

Special Issue: 联邦学习

• Regular Papers • Previous Articles     Next Articles

Federated visualization:a new model for privacy-preserving visualization

Yating WEI,Zhiyong WANG,Shuyue ZHOU,Wei CHEN()   

  1. State Key Lab of CAD&CG,Zhejiang University,Hangzhou 310058,China
  • Revised:2019-11-21 Online:2019-12-20 Published:2020-02-29
  • Supported by:
    The National Natural Science Foundation of China(61772456)

Abstract:

The concept,architecture,methods and applications of federated visualization were introduced.The federated visualization framework is capable of encrypting and training a visual model that reflect the characteristics of the entire data for specific tasks and scenarios.The federated visualization framework is an extension and application of federated learning,which emphasized using mutual benefit and win-win federal cooperation to visually analyze multi-source data under the premise of ensuring data privacy,towards breaking down data barriers in various fields and industries and realizing the sharing of data and knowledge.

Key words: federated learning, data privacy, visual feature, data visualization, artificial intelligence

CLC Number: 

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