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Books and Theses
- 2010
[b1]Marko Orescanin:
Complex shear modulus reconstruction using ultrasound shear-wave imaging. University of Illinois Urbana-Champaign, USA, 2010
Journal Articles
- 2024
- [j7]John Fischer
, Marko Orescanin, Eric Eckstrand:
VI-PANN: Harnessing Transfer Learning and Uncertainty-Aware Variational Inference for Improved Generalization in Audio Pattern Recognition. IEEE Access 12: 33347-33360 (2024) - [j6]Lucian Rombado, Marko Orescanin, Mara M. Orescanin:
Uncertainty-Aware Aerial Coastal Imagery Pattern Recognition Through Transfer Learning With ImageNet-1K Variational Embeddings. IEEE Access 12: 130866-130883 (2024) - [j5]Stephen Steckler, Marko Orescanin, Scott W. Powell, Pedro Ortiz, Veljko Petkovic:
Scaling Uncertainty Quantification From Patches to Scenes Through Discontinuity-Aware Stitching. IEEE Geosci. Remote. Sens. Lett. 21: 1-5 (2024) - 2023
- [j4]Marko Orescanin, Leslie N. Smith, Saurabh Sahu, Palash Goyal, Sujit Rokka Chhetri:
Editorial: Deep learning with limited labeled data for vision, audio, and text. Frontiers Artif. Intell. 6 (2023) - 2022
- [j3]James Bret Michael, Marko Orescanin:
Developing and Deploying Artificial Intelligence Systems. Computer 55(6): 15-17 (2022) - [j2]Marko Orescanin, Veljko Petkovic, Scott W. Powell, Benjamin R. Marsh, Sean C. Heslin:
Bayesian Deep Learning for Passive Microwave Precipitation Type Detection. IEEE Geosci. Remote. Sens. Lett. 19: 1-5 (2022) - [j1]Pedro Ortiz, Marko Orescanin, Veljko Petkovic, Scott W. Powell, Benjamin R. Marsh:
Decomposing Satellite-Based Classification Uncertainties in Large Earth Science Datasets. IEEE Trans. Geosci. Remote. Sens. 60: 1-11 (2022)
Conference and Workshop Papers
- 2024
- [c8]Lucian Rombado, Marko Orescanin, Mara Orescanin:
Visualizing Bayesian Convolutional Neural Network Uncertainty In Coastal Images with Grad-Cam Ensembling. IGARSS 2024: 1782-1785 - [c7]Stephen Steckler, Marko Orescanin, Pedro Ortiz, Veljko Petkovic:
Beyond Mean Squared Error: Alternative Loss Functions for Geoscience Image Regression with Neural Networks. IGARSS 2024: 7359-7362 - 2023
- [c6]Marko Orescanin, Brian Harrington, Derek Olson, Marc Geilhufe, Roy Edgar Hansen, Narada Warakagoda:
A Study on the Effect of Commonly Used Data Augmentation Techniques on Sonar Image Artifact Detection Using Deep Neural Networks. IGARSS 2023: 360-363 - [c5]Eleanor Casas, Pedro Ortiz, Marko Orescanin, Scott W. Powell, Malarvizhi Arulaj, Veljko Petkovic:
Utilizing Quantified Uncertainty in Synthetic Microwave Brightness Temperatures to Reveal Hidden Tropical Cyclone Structures. IGARSS 2023: 3768-3771 - [c4]Pedro Ortiz, Eleanor Casas, Marko Orescanin, Scott W. Powell, Veljko Petkovic:
Improving Deep Learning for Remote Sensing Research through a Bayesian Approach with Uncertainty Decomposition. IGARSS 2023: 5010-5013 - 2021
- [c3]Jason Henry, Mehmet Ergezer, Marko Orescanin:
Perceptually Constrained Fast Adversarial Audio Attacks. ICMLA 2021: 819-824 - [c2]Marko Orescanin, Mehmet Ergezer, Gurminder Singh, Matthew Baxter:
Federated Fine-Tuning Performance on Edge Devices. ICMLA 2021: 1174-1181 - 2020
- [c1]Nathan Thiem, Marko Orescanin, James Bret Michael:
Reducing Artifacts in GAN Audio Synthesis. ICMLA 2020: 1268-1275
Informal and Other Publications
- 2024
- [i3]John Fischer, Marko Orescanin, Eric Eckstrand:
VI-PANN: Harnessing Transfer Learning and Uncertainty-Aware Variational Inference for Improved Generalization in Audio Pattern Recognition. CoRR abs/2401.05531 (2024) - [i2]John Fischer, Marko Orescanin, Justin Loomis, Patrick McClure:
Federated Bayesian Deep Learning: The Application of Statistical Aggregation Methods to Bayesian Models. CoRR abs/2403.15263 (2024) - [i1]Donald W. Peltier III, Isaac Kaminer, Abram H. Clark, Marko Orescanin:
Swarm Characteristics Classification Using Neural Networks. CoRR abs/2403.19572 (2024)
Coauthor Index
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