2021 2nd International Conference on Computer Vision and Data Mining(ICCVDM 2021)
ICCVDM 2020 has successfully taken place on August 14-16 on Xi'an China! !


2020 International Conference on Computer Vision and Data Mining ( ICCVDM 2020 )


  The 2020 International Conference on Computer Vision and Data Mining has been held on August 14-16,2020 in Xi'an, China. All accepted papers were published by IOP Conference Series: Journal of Physics: Conference Series (JPCS)(ISSN:1742-6588) and have been indexed by EI, Scopus for indexing. ICCVDM 2020 focuses on Computer Science、Artificial Intelligence、Vision Science and Engineering、Software Process and Data Mining and so on.This conference aims to encourage exchange of information on research frontiers in different fields, connect the most advanced academic resources in China and abroad, turn research results into industrial solutions, bring together talents, technologies and capital to boost development. 


*Group photo


Keynote Speaker 1: 

Assoc. Prof. Bing Pan, Penn State Unversity, USA

Speech Title: Big Data Modeling in Tourism and Park Research


Keynote Speaker 2:

Prof. Daowen Qiu, School of Data and Computer Science, SYSU, China

Speech Title: A distributed semi-quantum computing model:A method of quantum-classical hybrid computing


Keynote Speaker 3:

Assoc. Prof. Wu Hao, Northwest Agricultural and Forestry University, China

Speech Title: Network-Based Methods for Mining Pathogenesis Pathways in Cancer


Keynote Speaker 4:

Prof. Tao Cheng, Guangxi University of Science and Technology, China

Speech Title: Wide spectrum denoising (WSD) for super-resolution microscopy imaging using compressed sensing and a high-resolution camera


Keynote Speaker 5:

Prof. Zhiyue Bo, Xi’an Jiaotong-Liverpool University, China

Speech Title: Big Data and China’s Approach to Net Zero Emission in 2050

主讲Rozmie Razif Othman.png

Keynote Speaker 6:

Dr. Rozmie Razif Othman, Universiti Malaysia Perlis (UniMAP), Perlis, Malaysia

Speech Title: Sequence Covering Array (SCA): The evolution of State Transition Testing