Best Student Paper Awards
15 June, 2020
Due to the high quality of the papers we have decided to offer 4 best student paper awards of 250 Euros (Springer cheques) each.
The papers of the 16th AIAI 2020 to receive the best student paper award and Springer cheques for books of 250 Euros each are:
- Autonomous Navigation for Drone Swarms in GPS-Denied Environments using Structured Learning by William Power, Zoran Obradovic, Martin Pavlovski, Daniel Saranovic, Ivan Stojkovic
- Arbitrary Scale Super-Resolution for Brain MRI Images by Chuan Tan, Jin Zhu, Pietro Lio
The papers of the 21st EANN to receive the best paper award and Springer cheques for books of 250 Euros each are:
- Leveraging Radar Features to Improve Point Clouds Segmentation with Neural Networks by Alessandro Cennamo, Florian Kaestner, Anton Kummert
- λ-DNNs and their Implementation in Aerodynamic and Conjugate Heat Transfer Optimization by Marina Kontou, Dimitrios Kapsoulis, Ioannis Baklagis, and Kyriakos Giannakoglou
The conference program for the virtual event is available; click below to view.
Proceedings have been published and all conference participants can download their personal copy from HERE. Password will be mailed directly to participants.
Update from the organisers
27 March, 2020
Dear colleagues of the AIAI community,
Developments in the Covid-19 virus have created a worldwide tragedy that we are watching on a daily basis hoping to end as soon as possible. After 16 years of holding AIAI, strong links have been developed with the members of our scientific community. This has been proven very clearly this year, with the high volume of submissions despite the major challenges facing our societies. We wish to thank you very much for that.
Human health is the most important asset of all. We are interested in the health and wellbeing of all our community, under the challenging circumstances that we are all facing.
In case the crisis ends in due time we still leave the option to hold the conference in the arranged venue open. If this is not the case, the conference will be held in a hybrid mode. Detailed information regarding the 16th AIAI 2020 will be announced on the website. We will also send you a relative email.
BEST STUDENT PAPER AWARDS
2 Scholarships (Springer cheques) of 500 Euros each will be given to the 2 Best Student Papers which can be used to purchase any Springer books desired.
Important Dates updated
Prof. John Macintyre
Pro Vice Chancellor at the University of Sunderland, United Kingdom
Professor Macintyre will give a plenary talk on the following subject:
AI Applications during the COVID-19 Pandemic – A Double Edged Sword
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).
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.
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.
Utilizing FPGA for AI acceleration without noticing it!
Prof. Yannis Papaefstathiou
Two years ago, an overview was presented in AIAI of how the designers can utilize FPGAs in their embedded systems, through the use of High-Level-Synthesis (HLS) Tools. In this presentation we will dive into the new development approaches that allow the designer to take full advantage of FPGAs, both in the Cloud and on the Edge, while barely noticing that their core processing is executed on reconfigurable logic. The new emerging design flow is based on seamlessly utilizing open-source accelerated libraries that are being optimized for execution on the new highly heterogeneous FPGA-based systems.
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.
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.
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).
H A L K I D I K I
P O R T O C A R R A S G R A N D R E S O R T
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