Author: nccmne

Ms Almira Suljovic, a student of the Faculty of Applied Sciences, defended her BSc Thesis in Electrical Engineering and Computer Science. The topic of the thesis work was the use of machine learning to detect diseased plants by processing images of the leaves. The work included creation of a prediction model as well as the integration of the model into a mobile application for the use by farmers. She has done her thesis work under the supervision of prof. Tomo Popovic, PhD, and mr Stevan Cakic, MSc.

ABSTRACT – Early detection and prevention are one of the biggest difficulties in the field of agriculture. Late detection of plant diseases or the use of wrong pesticides often leads to crop damage, reducing food quality. As the leaf is the best indicator of whether a plant is healthy or not, we can construct prediction models using machine learning to identify leaf status in the shortest possible time, thus preventing or reducing losses. This thesis shows how to determine leaf health status using the Detectron2 software library and the faster R-CNN neural network. The model was trained using a dataset with 6407 images. The initial dataset was extended using the RoboFlow tool. Google Colab, an environment for the development of cloud computing and machine learning, was used for testing and implementation. The practical application of the machine learning model was realized using an application developed using the Flutter platform.

Mr Bogdan Laban, a master student at the University of Donja Gorica, defended his Master thesis titled “Practical Use of Machine Learning in the Fight Against COVID-19”. The thesis was done at the Master academic studies “Information Management in Health Care” at the Faculty of International Economics, Finance and Business, under the supervision of his mentor prof. dr Tomo Popovic.

ABSTRACT – This study aims to find applicable combination of recent AI technologies and its uses during the COVID-19 pandemic. As AI has shown great improvements in the last few years, with many new feature-filled tools out on the market, it is almost certain that AI can help find ways to circumvent the dangers of COVID-19, in the form of noticing it, and preventing it. Authors cited in this work are AI professional, specializing in neural networks and their appliances in real world, in the form of visual processing and understanding, which will provide me with a solid hypothesis to base my master thesis on.

As this pandemic still has a solid grasp on the world, especially on less developed countries like Montenegro, I believe it makes a great testing ground for attributes like – percentage of people abiding pandemic specific laws (social distancing, mask wearing, etc.). Unfortunately, people of Montenegro are very divided on this issue, ranging from avid abiders, to those who completely ignore all safety procedures, even the most basic ones. As such, I believe this study will provide me with an insight into the right tools and tests for the residents of Montenegro, which vary a lot.