AIAI 2020

16th International Conference on Artificial Intelligence Applications and Innovations

Porto Carras Grand Resort, Halkidiki, Greece

5 – 7 June, 2020

AIAI 2020

16th International Conference on Artificial Intelligence Applications and Innovations

Porto Carras Grand Resort, Halkidiki, Greece

5 – 7 June, 2020

AIAI 2020

16th International Conference on Artificial Intelligence Applications and Innovations

Porto Carras Grand Resort, Halkidiki, Greece

5 – 7 June, 2020

AIAI 2020

16th International Conference on Artificial Intelligence Applications and Innovations

Porto Carras Grand Resort, Halkidiki, Greece

5 – 7 June, 2020

PROCEEDINGS

The proceedings of the AIAI 2020 will be published as always by the SPRINGER IFIP AICT Series and they are INDEXED BY SCOPUS, DBLP, Google Scholar, ACM Digital Library, IO-Port, MAthSciNet, CPCI, Zentralblatt MATH and EI Engineering Index

TO CONFIRM please visit the following Springer Link:
INFORMATION ON ABSTRACTING AND INDEXING

BEST PAPER AWARDS

ONE BEST PAPER AWARD of 150 Euros cash will be given to the best student EANN/AIAI 2020 paper
by the General co-Chair PROFESSOR JOHN MACINTYRE (University of Sunderland).

BIBLIOMETRIC DETAILS

We proudly announce that according to Springer’s statistics, the last 13 AIAI conferences have been downloaded 1,143,372 (more than 1 million times!!).

For more Bibliometric Details Please click … AIAI BIBLIOMETRIC DETAILS

T U T O R I A L S

Artificial Intelligence for Cloud Computing Management

Prof. Vincenzo Piuri

This talk will discuss a user-centric, dependability- and resilience-driven framework that considers deploying and protecting users’ applications in the Cloud infrastructure so as to minimize their exposure to the vulnerabilities in the network, as well as offering fault tolerance and resilience as a service to the users who need to deploy their applications in the Cloud.

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AI/ML for games for AI/ML

Dr Kostas Karpouzis

In this tutorial, we will discuss both approaches that relate AI/ML to games: starting from a theoretical review of user/player modelling concepts, we will discuss how we can collect data from the users during gameplay and use them to adapt the player experience or model the players themselves. Following that, we will discuss AI/ML algorithms used to train computer-based players and how these can be used in contexts outside gaming. Finally, we will discuss player modelling in contexts related to serious gaming, such as health and education.

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W O R K S H O P S

9th Mining Humanistic Data Workshop

The Mining Humanistic Data Workshop (MHDW) aims to bring together interdisciplinary approaches that focus on the application of innovative as well as existing artificial intelligence, data matching, fusion and mining and knowledge discovery and management techniques to data derived from all areas of Humanistic Sciences.

Visit website – More info – Submission

5th Workshop on “5G – Putting Intelligence to the Network Edge” (5G-PINE 2020)

The 5th 5G-PINE Workshop has been established to disseminate knowledge obtained from actual EU projects as well as from any other action of EU-funded research, in the wider thematic area of “5G Innovative Activities – Putting Intelligence to the Network Edge” and with the aim of focusing on Artifical Intelligence (AI) in modern 5G telecommunications infrastructures.

Visit websiteMotivationSubmission

Machine Learning and Computational Intelligence in multi-omics and medical image analysis (MALCI_MUOMI 2020)

There is an increasing need for the application of Machine Learning (ML) and Computational Intelligence (CI) techniques, which can effectively perform image processing operations (such as segmentation, co-registration, classification, and dimensionality reduction), in the fields of neuroimaging and oncological imaging. Although the manual approach often remains the golden standard in some tasks (e.g., segmentation), ML can be exploited to automate and facilitate the work of researchers and clinicians. Frequently used techniques include Support Vector Machines (SVMs) for classification problems, graph-based methods, and Artificial Neural Networks (ANNs).

More infoSubmission

H A L K I D I K I

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