activity
20232026
most citedDeep Learning Methods for Retinal Blood Vessel Segmentation: Evaluation on Images with Retinopathy of Prematurity

16 citations · 19 across the 7 of their papers we have counts for

collaborators

7 papers

eess.SP2026

Task-Oriented Wireless Transmission of 3D Point Clouds: Geometric Versus Semantic Robustness

Vukan Ninkovic, Tamara Sobot, Vladimir Vincan +3

Wireless transmission of high-dimensional 3D point clouds (PCs) is increasingly required in industrial collaborative robotics systems. Conventional compression methods prioritize g…

cs.CL2025

Improving Customer Service with Automatic Topic Detection in User Emails

Bojana Bašaragin, Darija Medvecki, Gorana Gojić +2

This study introduces a novel natural language processing pipeline that enhances customer service efficiency at Telekom Srbija, a leading Serbian telecommunications company, throug…

eess.IV2023★ 16 cited

Deep Learning Methods for Retinal Blood Vessel Segmentation: Evaluation on Images with Retinopathy of Prematurity

Gorana Gojić, Veljko Petrović, Radovan Turović +4

Automatic blood vessel segmentation from retinal images plays an important role in the diagnosis of many systemic and eye diseases, including retinopathy of prematurity. Current st…

eess.IV2023★ 1 cited

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…

cs.LG2023★ 1 cited

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…

cs.LG2023★ 1 cited

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…

cs.LG2023

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.…