23 citations · 47 across the 16 of their papers we have counts for
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Application of Deep Learning Methods in Monitoring and Optimization of Electric Power Systems
Ognjen Kundacina
This PhD thesis thoroughly examines the utilization of deep learning techniques as a means to advance the algorithms employed in the monitoring and optimization of electric power s…
Overview of Deep Learning Methods for Retinal Vessel Segmentation
Gorana Gojić, Ognjen Kundačina, Dragiša Mišković +1
Methods for automated retinal vessel segmentation play an important role in the treatment and diagnosis of many eye and systemic diseases. With the fast development of deep learnin…
Non-adversarial Robustness of Deep Learning Methods for Computer Vision
Gorana Gojić, Vladimir Vincan, Ognjen Kundačina +2
Non-adversarial robustness, also known as natural robustness, is a property of deep learning models that enables them to maintain performance even when faced with distribution shif…
Graph Neural Networks on Factor Graphs for Robust, Fast, and Scalable Linear State Estimation with PMUs
Ognjen Kundacina, Mirsad Cosovic, Dragisa Miskovic +1
As phasor measurement units (PMUs) become more widely used in transmission power systems, a fast state estimation (SE) algorithm that can take advantage of their high sample rates…
Scalability and Sample Efficiency Analysis of Graph Neural Networks for Power System State Estimation
Ognjen Kundacina, Gorana Gojic, Mirsad Cosovic +2
Data-driven state estimation (SE) is becoming increasingly important in modern power systems, as it allows for more efficient analysis of system behaviour using real-time measureme…
Supporting Future Electrical Utilities: Using Deep Learning Methods in EMS and DMS Algorithms
Ognjen Kundacina, Gorana Gojic, Mile Mitrovic +2
Electrical power systems are increasing in size, complexity, as well as dynamics due to the growing integration of renewable energy resources, which have sporadic power generation.…
GP CC-OPF: Gaussian Process based optimization tool for Chance-Constrained Optimal Power Flow
Mile Mitrovic, Ognjen Kundacina, Aleksandr Lukashevich +4
The Gaussian Process (GP) based Chance-Constrained Optimal Power Flow (CC-OPF) is an open-source Python code developed for solving economic dispatch (ED) problem in modern power gr…