News Archives - Page 13 of 36 - EuroCC Montenegro

27.06.2023.03.07.2023.

Master thesis: Computer vision and AI in medicine

Mr Dejan Babic, a young researcher from UDG, just defended his Master thesis on the use of computer vision and artificial intelligence in medicine. This is a great example of using ICT for vertical priority domains of Monteengrin S3. This research was supported in part by HPC4S3ME project and EUROCC. Mr Babic intends to continue his research in this domain and to enroll PhD program at the UDG. Mr Babic explored the use of different tools for ML and he also experimened with the use of HPC for training prediction models that can be used in medicine. He was one of the first MSc theses defended from the Artificial Intelligence Master program created under the EuroCC project.

ABSTRACT – Artificial Intelligence is transforming the way we live, work, and communicate with the world. The proliferation of data has been the biggest driver of AI in recent years. AI in medicine is rapidly developing and holds great potential in revolutionizing healthcare systems. Its application is already producing promising results in disease detection, diagnosis and drug discovery. AI is widely used in medical facilities worldwide as a decision support tool for patient diagnosis. It is expected to bring significant benefits to healthcare sector. In this thesis, the focus is on the application of artificial intelligence and computer vision in solving real medical problems. The research is both theoretical and empirical and focuses on the application of artificial intelligence and computer vision in the detection of pneumonia, segmentation of blood vessels in the retina, and estimation of cardiovascular risk. The main goal of the research is to achieve the highest possible accuracy in specific cases and approaches, in order for these approaches to be considered applicable in medicine. Throughout the study, some of the ethical issues related to the use of this technology were also raised. At the end of the study, the results, potential challenges, and future directions of this research were discussed.

Computer vision and artificial intelligence in medicine

Segmentation of blood vessels in images of retina

27.06.2023.03.07.2023.

Master thesis: The use of Artificial Intelligence on Edge

Mr Ivan Jovovic, a young researcher from UDG, just defended his Master thesis on the use of artificial intelligence and machine learining on edge devices. This research was supported in part by HPC4S3ME project and EUROCC. Mr Jovovic intends to continue his research in this domain and to enroll PhD program at the UDG. Mr Jovovic explored the use of different tools for ML and he also experimened with the use of HPC for training prediction models that can be ported onto edge devices. He was one of the first MSc theses defended from the Artificial Intelligence Master program created under EuroCC project.

ABSTRACT – This thesis explores the combination of artificial intelligence, machine learning, deep learning, and edge computing in modern applications, with a special focus on medicine and agriculture. The paper first introduces the reader to the basic terms and definitions of machine learning, deep learning, computer vision, the Internet of Things and Edge computing. After the theoretical basis, the work provides an insight into the practical applications of these technologies in medicine and agriculture, highlighting the benefits and drawbacks of their applications. In the following, the paper offers a detailed study of practical examples of edge artificial intelligence in agriculture and healthcare, as well as artificial intelligence in the field of medicine, with focus on disease classification. Through the realization and implementation of these projects, the interpretation of the results and the discussion, the paper emphasizes the importance of the integration of artificial intelligence and edge computing in various industries.

Master thesis: The use of Artificial Intelligence on Edge (Edge AI)

10.06.2023.04.07.2023.

IT2023 and EuroCC2 featured in IEEE Region 8 News

Thanks to EuroCC2 team from Montenegro, EuroCC and 27th International Scientific and Professional Conference – Information technology IT2023 were featured in the June issue of IEEE Region 8 News magazine (Vol 4 No 2). You can access the full issue at the following link. The News bulletin is published quartterly and distributed to over 80000 IEEE members in Region 8.

EuroCC2 and IT2023 featured in IEEE Reggion8 News

06.06.2023.07.06.2023.

EuroCC2 Twinning opportunities with NCC Cyprus

Representatives from the NCCs of Montenegro and Cyprus (CaSToRC), held an initial meeting on June 6, 2023, with the primary purpose to explore potential cooperation, knowledge sharing opportunities and best practice exchange through effective peer’s cooperation and Twinning activities.

During the meeting, the NCCs’ teams expressed mutual interest in exchanging experiences and learning opportunities, particularly in the areas of productive industrial cooperation and HPC/AI related training activities. Additionally, they discussed the exchange of operational practices and proven initiatives related to NCC management, cooperation and communication activities.

The next steps involve organizing administrative, logistic and operational support to facilitate team visits and work program with shared topics’ interest. By leveraging NCCs’ respective expertise and synergizing their efforts, both NCCs aim to strengthen their capacities and effectively address HPC+ needs/potential in their national ecosystems.

29.05.2023.08.06.2023.

Open call for grants by the Ministry of Science and Technological Development

An information session and workshop was held at the University of Donja Gorica on May 26 starting to promote and clarify the conditions of the Competition for the co-financing of national scientific research projects by the Ministry of Science and Technological Development.

On behalf of the Ministry of Science and Technological Development, Ms. Milena Milonjić, Acting Director General of the Directorate for Scientific Research, Ms. Jelena Šaranović and Ms. Zorana Lakićević-Milutinović addressed the audience and presented the Competition – open call rules and criteria for co-financing national scientific research projects for 2023.
About 40 researchers, professors and associates of the University of Donja Gorica attended the informative and interactive session.

A grat opportunity for HPC and AI researchers to apply for this open call

The main goal of this open call is to strengthen the capacity of research teams in Montenegro, in order to encourage excellence, thereby contributing to the development of a society based on knowledge and competitiveness at the international level.

27.05.2023.27.05.2023.

AIMHiGH project featured in Success Story booklet by EUROCC

EuroCC has published their first booklet edition of Success Stories for 2023! The booklet contains a summary of successful experiments that have been conducted within the EuroCC projects with some of them using EuroHPC Joint Undertaking supercomputers Each success story includes its challenges, solutions, business impacts and benefits. Discover more on the newly published booklet! Project AIMHiGH, a HPC/AI use case for computer vision solutions in agri-food sector, was featured in this first bulletin. The booklet is available at the following link.

Project AIMHIGH featured in the Success Story bulletin

25.05.2023.26.05.2023.

A journal paper: Machine Learning Models for Statistical Analysis

Researchers from UDG and NCC Montenegro published a paper “Machine Learning Models for Statistical Analysis” by M. Grebovic et al. in The International Arab Journal of Information Technology, Vol. 20, No. 3A, Special Issue 2023. This was a follow up effort on the paper previously presented at the ACIT2023 conference.

ABSTRACT – Compared to traditional statistical models, Machine Learning (ML) algorithms provide the ability to interpret, understand and summarize patterns and regularities in observed data for making predictions in an advanced and more sophisticated way. The main reasons for the advantage of ML methods in making predictions are a small number of significant predictors of the statistical models, which means limited informative capability, and pseudo-correct regular statistical patterns, used without previous understanding of the used data causality. Also, some ML methods, like Artificial Neural Networks, use non-linear algorithms, considering links and associations between parameters. On the other hand, statistical models use one-step-ahead linear processes to improve only short-term prediction accuracy by minimizing a cost function. Although designing an optimal ML model can be a very complex process, it can be used as a potential solution for making improved prediction models compared to statistical ones. However, ML models will not automatically improve prediction accuracy, so it is necessary to evaluate and analyze several statistical and ML methods, including some artificial neural networks, through accuracy measures for prediction purposes in various fields of applications. A couple of techniques for improving suggested ML methods and artificial neural networks are proposed to get better accuracy results.

The paper is available at the following link.