Ivana Miličić

Ivana Miličić

Position:Junior Research Assistant in CIT

Academic Rank: Junior research assistant

Ivana Miličić is a third-year PhD student in Computing and Control Engineering at the Faculty of Technical Sciences, University of Novi Sad, and Junior Research Assistant at BioSense Institute. She obtained a bachelor’s degree in Biomedical Engineering and a master’s degree in Computing and Control Engineering from the same faculty. During her studies, she gained knowledge in the field of machine learning, which she expanded to deep learning. Her current research focus is on explainable artificial intelligence, with the goal of gaining a better understanding of how models make decisions, as well as evaluating their trustworthiness and potential applications in solving problems in areas such as agriculture and biomedicine.

Center:

proba 2

CIT

  1. Miličić, Ivana; Pajević, Nina; Stefanović, Dimitrije; Panić, Marko; Šikoparija, Branko; Sarda-Estève, Roland; Guinot, Benjamin; Djuric, Nemanja.(2025). Evaluation of Training Strategies for Ambrosia Pollen Detection on Outdoor Images, 14th Int’l Symposium on Image and Signal Processing and Analysis (ISPA 2025), Coimbra, Portugal. DOI: 10.1109/ISPA66905.2025.11259450
  2. Smajlhodžić-Deljo, M., Hundur Hiyari, M., Gurbeta Pokvić, L., Merdović, N., Bećirović, F., Spahić, L., Grbović, Ž., Stefanović, D., Miličić, I., & Marko, O. (2024). Using Data-Driven Computer Vision Techniques to Improve Wheat Yield Prediction. AgriEngineering,6(4),4704-4719. DOI: https://doi.org/10.3390/agriengineering6040269
  3. I. Miličić, Ž. Grbović, M. Buđen, N. Stevanović, N. Stanković, and M. Panić, Optimal Selection of Locations for Wheat Ear Smartphone Sampling Using UAV Multispectral Data, 2024 32nd Telecommunications Forum (TELFOR), Belgrade, Serbia, 2024, pp. 1-4, DOI: 10.1109/TELFOR63250.2024.10819153.
  4. Miličić, I., Pajević, N., & Ivošević, B. (2024). Comparative Analysis of Unmanned Aerial Vehicle Land Cover Classification of Two Study Sites in Serbia. International Conference of Environmental Remote Sensing and GIS, 2024, 113–116. https://doi.org/10.5281/zenodo.11584526