The Association of Applied Psychology Students “Axon” continues a series of three multidisciplinary lectures entitled “The Era of Artificial Intelligence”.
A lecture by Ms Irena Jerkovic from Zagreb
On that occasion, on Friday, March 18, at 3 pm, via the Zoom platform, our guest Irena Jerković from Zagreb will hold a lecture on “How to make emotionally intelligent AI”. Irena Jerković is a psychologist, founder and co-founder of two start-ups CrevPulse and Improv3, CPO at TalentLift, an enthusiast for building emotionally intelligent AI technology that can improve people’s quality of life.
Young researchers from UDG participated in the event
Scientific conference “Information and Communication Technologies – Current state and Perspectives”, on “Deep Machine Learning”, organized by the Committee for Information and Communication Technologies of the Montenegrin Academy of Sciences and Arts and co-organized by the University of Montenegro, will be held on Monday, March 21, 2022, at the Rectorate of the University of Montenegro, starting at 11 am. The agenda for the event is available here.
EuroCC NCC Montenegro and AIMHiGH projects will be featured in the presentation “Development of IoT Edge Computer Vision Sensors for Smart Farms Supported by HPC and AI”.
“Deep Machine Learning” conference organized by the Montenegrin Academy of Sciences and Arts
A paper titled “Face Mask Detection Based on Machine Learning and Edge Computing”, authored by I. Jovovic, D. Babic, S. Cakic, T. Popovic, S. Krco, and P. Knezevic, was presented at the 2022 21th International Symposium INFOTEH-JAHORINA. The paper was presented by a young researcher Mr Ivan Jovovic, Faculty for Information Systems and Technologies, on 18 March 2022. The paper discussed the use of machine learning for face mask detection and porting of prediction models onto the edge Ai platform. The effort was supported by the EuroCC Monteengro team link.
Presentation of the paper in the virtual online session of the conference
ABSTRACT – This paper describes research effort aimed at the use of machine learning, Internet of Things, and edge computing for a use case in health, mainly the prevention of the spread of infectious diseases. The main motivation for the research was the Covid-19 pandemic and the need to improve control of the prevention measures implementation. In the study, the experimentation was focused on the use of machine learning to create and utilize prediction models for face mask detection. The prediction model is then evaluated on the various platforms with a focus on the use on various edge devices equipped with a video camera sensor. Different platforms have been tested and evaluated such as standard laptop PC, Raspberry Pi3, and Jetson Nano AI edge platform. Finally, the paper discusses a possible approach to implement a solution that would utilize the face mask detection function and lays out the path for the future research steps.
The paper was presented at the IEEE 2022 21st INFOTEH-JAHORINA Conference
A paper titled “Detection of Plant Diseases Using Leaf Images and Machine Learning”, authored by A. Suljovic, S. Cakic, T. Popovic and S. Sandi, was presented at the 2022 21th International Symposium INFOTEH-JAHORINA. The paper was presented by a young researcher Ms Almira Suljovic, Faculty of Applied Sciences, on 18 March 2022 in the paper presentation session. The paper discussed the use of machine learning for detection of plant diseases that could be used in agriculture. The effort was supported by the EuroCC Monteengro team link.
Paper presented in the afternoon session by Ms Almira Suljovic
ABSTRACT – Prevention and early detection of plant diseases is one of the main issues and challenges in agriculture. Farmers spend a lot of time observing and detecting diseased plants, often by looking at and analyzing plant leaves. Inadequate handling of plant disease such as late detection or the use of wrong pesticides often causes damage to crops, which causes a deterioration in the quality of food. This problem could be addressed using artificial intelligence and machine learning to detect plant diseases by processing digital images of leaves. As the leaf is the best indicator of whether the plant is healthy or not, by applying machine learning we can create predication models to detect the condition of the leaf in a shorter period of time and possibly prevent or reduce the losses. This paper describes experimenting with Detectron2 software library and Faster R-CNN neural network in order to detect the condition of the leaf. A dataset containing 6407 images was used to train the model. The original dataset has been extended by augmenting images using the RoboFlow tool. The experimentation and implementation was done using Google Colab, environment designed for cloud computing and machine learning development.
Paper presented at the IEEE 2022 21st INFOTEH-JAHORINA Conference
On 16-17 March, FF4EuroHPC partners have started with a two-day project review. Dr Bastian Koller, managing director at HLRS – High-Performance Computing Center Stuttgart and project coordinator started the public presentation of the FF4EuroHPC project insights. He also gave a glimpse into the Experiments supported by FF4EuroHPC and provided the outlooks for the future. But most of all, he presented clearly how this project supports European SMEs and encourages their competitiveness and highlighted the added value project brings to the European HPC landscape (source: FF4EuroHPC).
Project AIMHiGH was presented in the session dedicated to FF4EuroHPC experiments
In the photo below, you can see the outstanding results our consortia gained – red-colored countries are participating in the FF4EuroHPC Experiments. Learn more about the Experiments at the foll.owing link.
The Romanian National Competence Center in HPC – RoNCC together with the National Competence Centre in Montenegro are pleased to invite you to the workshop “Fostering sustainable agriculture through High performance Computing”, organized on March 16, at 11:00, in online format. The aim of the event is to disseminate to users the benefits of using HPC (High Performance Computing), HPDA (High Performance Data Analysis) and AI technologies in agriculture and to present the multiple development possibilities by adopting HPC in innovation activities and projects, by sharing uses. houses and good practices. The webinar is aimed at existing or potential users of HPC, HPDA and AI in the private sector (SMEs, start-ups) as well as in the public sector (universities, public administration, research institutions, etc.), whose projects and activities fall in the field of AGRICULTURE AND RURAL DEVELOPMENT. Please check Romanian NCC website at: https://roncc.ro/
NCC Montenegro representatives will be giving presentation on the use of HPC and AI in agriculture, namely we will be discussing the projects currently implemented by UDG and partner organizations. Agenda for the event is available at the following link.
Young researchers, Ms Almira Suljovic and Mr Ivan Jovovic, from UDG will be presenting their papers at the upcoming IEEE INFOTEH 2022 Conference. This is the 21st International Symposium INFOTEH-JAHORINA. The first paper will be discussing the use of machine learning to detect disease in leafs with potential application in smart agriculture. The other paper will be discussing the use of machine learning to detect face masks and the use of prediction models on edge AI devices. The papers to be presented are scheduled for 18 March 2022 and both papers discuss the use of AI and machine learning. More about the conference can be found at the following link.
NCC Montenegro provided support to these researchers and they plan to continue the experimentation in these fields using HPC resources. The list of accepted papers and the conference program are available here.
