Deep and machine learning are the state-of-the-art at providing models, methods, tools and techniques for developing autonomous and intelligent systems which can revolutionize industrial and commercial applications in various fields such as online commerce, intelligent transportation, healthcare and medicine, security, manufacturing, education, games, and various other industrial applications. All such fields produce and consume massive amount of big data, which include, for example, online commerce data (marketing data, customer reviews, customer relationship), transportation data (road sensors, cameras, GPS), and data about healthcare, social media, and various other applications. Deep learning techniques and big data techniques yield useful outputs in predicting, discovering and acquiring insights and deeper knowledge about events for better and efficient decision making. The groundbreaking technology of blockchain technology also enable decentralization, immutability, and transparency of data and applications. It has been exploited in modern research and industrial domains in order to achieve high level of trust, security and reliable execution of applications and data which are shared across a network of computers.
The International Conference on Deep Learning, Big Data and Blockcain (DEEP-BDB) aims to enable synergy between these areas and to provide a leading forum for researchers, developers, practitioners, and professional from public sectors and industries in order to meet and share latest solutions and ideas in solving cutting edge problems in modern information society and economy. The conference comprises a set of tracks that focus on specific challenges in deep (and machine) learning, big data and blockchain.
All papers accepted for this conference are to be published by Springer in the Advances in Intelligent Systems and Computing series . The proceedings (books) of this series are submitted to ISI Proceedings, EI-Compendex, DBLP, SCOPUS, Google Scholar and Springerlink.
DEEP-BDB 2020 is co-located with the FiCloud 2021 and MobiWis 2021 conferences.
With Support of:
      
      
         
         
Deep and machine learning are the state-of-the-art at providing models, methods, tools and techniques for developing autonomous and intelligent systems which can revolutionize industrial and commercial applications in various fields such as online commerce, intelligent transportation, healthcare and medicine, security, manufacturing, education, games, and various other industrial applications. All such fields produce and consume massive amount of big data, which include, for example, online commerce data (marketing data, customer reviews, customer relationship), transportation data (road sensors, cameras, GPS), and data about healthcare, social media, and various other applications. Deep learning techniques and big data techniques yield useful outputs in predicting, discovering and acquiring insights and deeper knowledge about events for better and efficient decision making. The groundbreaking technology of blockchain technology also enable decentralization, immutability, and transparency of data and applications. It has been exploited in modern research and industrial domains in order to achieve high level of trust, security and reliable execution of applications and data which are shared across a network of computers.
The International Conference on Deep Learning, Big Data and Blockcain (DEEP-BDB) aims to enable synergy between these areas and to provide a leading forum for researchers, developers, practitioners, and professional from public sectors and industries in order to meet and share latest solutions and ideas in solving cutting edge problems in modern information society and economy. The conference focuses on specific challenges in deep (and machine) learning, big data and blockchain. Topics of interest include (but not limited to):
Submission Deadline | 10 March 2021 |
Authors Notification | 20 May 2021 |
Final Manuscript Due | 15 June 2021 |
Markus Aleksy, ABB, Germany
Irfan Awan, University of Bradford, UK
Salima Benbernou, Paris Descartes University, France
Flora Amoto, University of Naples "Federico II", Italy
Francesco Piccialli, University of Naples "Federico II", Italy
Muhammad Younas, Oxford Brookes University, UK
Journal Special Issue CoordinatorSatish Narayana, University of Tartu, Estonia
Workshop CoordinatorFilipe Portela, University of Minho Portugal, Portugal
Publicity ChairMourad Ouziri, Paris Descartes University, France
Papers must be written in English. Full papers should be limited to 12 pages. Short papers should be limited to 8 pages. Papers must be formatted in Springer's format. See Information for Authors of Springer Proceedings .
All papers accepted for this conference are peer-reviewed and are to be published by Springer in the Advances in Intelligent Systems and Computing series .
Submitted research papers may not overlap with papers that have already been published or that are simultaneously submitted to a journal or a conference with proceeding
In order to submit your paper click on the link to EasyChair submission system: Submission Link
Note: To submit a paper you need to have an EasyChair account. Follow the link EasyChair Signup to create EasyChair account, if needed.
Registrations for the conference and workshops are done online. Participants may pay instantly using their credit cards or they may choose to pay through the bank transfer.
Details of the registration will be published.
High quality papers will be considered for publication in the following special issue. Authors are invited to submit extended versions of the papers that must contain significant amount of new material such as new experiments, results, and related work. All papers submitted to the special issue will be reviewed by multiple reviewers.
Special Issue on: Cloud, IoT and Data Science
Information Systems Frontiers, Springer
Impact Factor = 3.630 (2019)
Five year impact factor = 4.016 (2019)
The conference program is planned to include:
Details of the program will be published later.
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