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2023 International Conference on Deep Learning and Data Management (DLDM 2023)


24 - 25 November 2023 - Shanghai, China
Online Paper Submission

ABOUT CONFERENCE

As one of the most exciting and fast-growing techniques in Artificial Intelligence, deep learning becomes the most state-of-the-art technique taking responsible for a significant number of recent breakthroughs in related areas. But the deep learning models are highly dependent on the underlying data. Thus, data management principles and practices need to be adopted throughout the development process of deep learning models. Thus data management in deep learning is of great importance for deep learning community as well as for data scientists.
Organized by Hubei Zhongke Institute of Geology and Environment Technology, 2023 International Conference on Deep Learning and Data Management (DLDM 2023) will be held on Nov. 24th-25th, 2023 in Shanghai, China. This event is an international forum for researchers, scientists, and professionals from both academia and industry to exchange up-to-date knowledge and experience in different fields of AI and data management to discuss and exchange information and knowledge in their areas of interest. Featured with keynote session, technical session, social networking event and exhibition, DLDM 2023 will provide the delegates an unparalleled opportunity to exchange with qualified professionals and build future partnership.
Looking forward to your participation.

IMPORTANT DATES

20 April 2023

Paper submission Deadline

30 June 2023

Early Registration Deadline

30 September 2023

Late Registration Deadline

24 - 25 November 2023

Conference Dates

BE THE BEST PRESENTER

Be the Best Presenter and Best Student in an International Conference. Get rewards to your commitment, knowledge and be a partner to revolutionize the research by building the arch of knowledge.

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WHO SHOULD ATTEND

Our conference is designed for members of the academia and non-profit, public, and private sector members who are interested in the latest research and academic developments in the field of deep learning and data management

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Topics include but not limited to

Deep learning based models and algorithms
Deep learning architectures
Data analysis, insights and hidden pattern
Data analysis and decision making
Data wrangling, munching and cleaning
Data integration and fusion
Data visualization
Data and information quality
Data security and privacy
Data classification and clustering
Security threat detection
Data search and mining
...

Call for Papers

DISCOVER SHANGHAI

City Tour In SHANGHAI

Shanghai is one of the four direct-controlled municipalities of China and the most populous city in the world, with a population of more than 24 million as of 2017. It is a global financial centre and transport hub, with the world's busiest container port. Located in the Yangtze River Delta, it sits on the south edge of the estuary of the Yangtze in the middle portion of the East China coast.

As a major administrative, shipping and trading city, Shanghai grew in importance in the 19th century due to trade and recognition of its favourable port location and economic potential. It has re-emerged as a hub for international trade and finance; it is the home of the Shanghai Stock Exchange, one of the world's largest by market capitalization.

Shanghai has been described as the "showpiece" of the booming economy of mainland China; renowned for its Lujiazui skyline, and museums and historic buildings, such as those along The Bund, as well as the City God Temple and the Yu Garden.

REGISTRATION

Early Registration
Deadline: 30 June 2023
  • Authors (Students): 500USD/3200RMB
  • Authors (Regular): 550USD/3500RMB
  • Listener: 200USD/1200RMB
  • Virtual Delegate: 150USD/1000RMB
  • Extra Paper: 450USD/3000RMB

Late Registration
Deadline: 30 September 2023
  • Authors (Students): 550USD/3500RMB
  • Authors (Regular): 600USD/3800RMB
  • Listener: 235USD/1500RMB
  • Virtual Delegate: 200USD/1200RMB
  • Extra Paper: 500USD/3200RMB

Venue: SJTU Academic Exchange Center

Shanghai Jiao Tong University, Shanghai, China 

Register

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Contact Details

18696182515

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