Complex shear modulus reconstruction using ultrasound shear-wave imaging - Marko Orescanin (2010)

Reducing Artifacts in GAN Audio Synthesis. - Nathan Thiem; Marko Orescanin; James Bret Michael (ICMLA, 2020)

Perceptually Constrained Fast Adversarial Audio Attacks. - Jason Henry; Mehmet Ergezer; Marko Orescanin (ICMLA, 2021)

Federated Fine-Tuning Performance on Edge Devices. - Marko Orescanin; Mehmet Ergezer; Gurminder Singh; Matthew Baxter (ICMLA, 2021)

Developing and Deploying Artificial Intelligence Systems. - James Bret Michael; Marko Orescanin (Computer, 2022)

Bayesian Deep Learning for Passive Microwave Precipitation Type Detection. - Marko Orescanin; Veljko Petkovic; Scott W. Powell; Benjamin R. Marsh; Sean C. Heslin (IEEE Geosci. Remote. Sens. Lett., 2022)

Decomposing Satellite-Based Classification Uncertainties in Large Earth Science Datasets. - Pedro Ortiz; Marko Orescanin; Veljko Petkovic; Scott W. Powell; Benjamin R. Marsh (IEEE Trans. Geosci. Remote. Sens., 2022)

Utilizing Quantified Uncertainty in Synthetic Microwave Brightness Temperatures to Reveal Hidden Tropical Cyclone Structures. - Eleanor Casas; Pedro Ortiz; Marko Orescanin; Scott W. Powell; Malarvizhi Arulaj; Veljko Petkovic (IGARSS, 2023)

A Study on the Effect of Commonly Used Data Augmentation Techniques on Sonar Image Artifact Detection Using Deep Neural Networks. - Marko Orescanin; Brian Harrington 003; Derek Olson; Marc Geilhufe; Roy Edgar Hansen; Narada Warakagoda (IGARSS, 2023)

Improving Deep Learning for Remote Sensing Research through a Bayesian Approach with Uncertainty Decomposition. - Pedro Ortiz; Eleanor Casas; Marko Orescanin; Scott W. Powell; Veljko Petkovic (IGARSS, 2023)

Editorial: Deep learning with limited labeled data for vision, audio, and text. - Marko Orescanin; Leslie N. Smith; Saurabh Sahu; Palash Goyal; Sujit Rokka Chhetri (Frontiers Artif. Intell., 2023)

Turn Down the Noise: Perceptually Constrained Attacks for Multi-Label Audio Classification. - Erick Capulong; Marko Orescanin; Pedro Ortiz; Patrick McClure (ICMLA, 2024)

Visualizing Bayesian Convolutional Neural Network Uncertainty In Coastal Images with Grad-Cam Ensembling. - Lucian Rombado; Marko Orescanin; Mara Orescanin (IGARSS, 2024)

Beyond Mean Squared Error: Alternative Loss Functions for Geoscience Image Regression with Neural Networks. - Stephen Steckler; Marko Orescanin; Pedro Ortiz; Veljko Petkovic (IGARSS, 2024)

VI-PANN: Harnessing Transfer Learning and Uncertainty-Aware Variational Inference for Improved Generalization in Audio Pattern Recognition. - John Fischer; Marko Orescanin; Eric Eckstrand (IEEE Access, 2024)

Federated Bayesian Deep Learning: The Application of Statistical Aggregation Methods to Bayesian Models. - John Fischer; Marko Orescanin; Justin Loomis; Patrick McClure (IEEE Access, 2024)

Uncertainty-Aware Aerial Coastal Imagery Pattern Recognition Through Transfer Learning With ImageNet-1K Variational Embeddings. - Lucian Rombado; Marko Orescanin; Mara M. Orescanin (IEEE Access, 2024)

Scaling Uncertainty Quantification From Patches to Scenes Through Discontinuity-Aware Stitching. - Stephen Steckler; Marko Orescanin; Scott W. Powell; Pedro Ortiz; Veljko Petkovic (IEEE Geosci. Remote. Sens. Lett., 2024)

Swarm Characteristic Classification using Robust Neural Networks with Optimized Controllable Inputs. - Donald W. Peltier III; Isaac Kaminer; Abram H. Clark; Marko Orescanin (CoRR, 2025)

Swarm Characteristics Classification Using Neural Networks. - Donald W. Peltier III; Isaac Kaminer; Abram H. Clark; Marko Orescanin (IEEE Trans. Aerosp. Electron. Syst., 2025)