Marko Orescanin

According to our database, Marko Orescanin authored at least 18 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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 Characteristics Classification Using Neural Networks.

Donald W. Peltier III, Isaac Kaminer, Abram H. Clark, Marko Orescanin

CoRR, 2024

Federated Bayesian Deep Learning: The Application of Statistical Aggregation Methods to Bayesian Models.

John Fischer, Marko Orescanin, Justin Loomis, Patrick McClure

CoRR, 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

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

Beyond Mean Squared Error: Alternative Loss Functions for Geoscience Image Regression with Neural Networks.

Stephen Steckler, Marko Orescanin, Pedro Ortiz, Veljko Petkovic

Proceedings of the IGARSS 2024, 2024

Visualizing Bayesian Convolutional Neural Network Uncertainty In Coastal Images with Grad-Cam Ensembling.

Lucian Rombado, Marko Orescanin, Mara Orescanin

Proceedings of the IGARSS 2024, 2024

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., February, 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

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 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, Derek Olson, Marc Geilhufe, Roy Edgar Hansen, Narada Warakagoda

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

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

Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2023

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

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

Developing and Deploying Artificial Intelligence Systems.

James Bret Michael, Marko Orescanin

Computer, 2022

2021

Federated Fine-Tuning Performance on Edge Devices.

Marko Orescanin, Mehmet Ergezer, Gurminder Singh, Matthew Baxter

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

Perceptually Constrained Fast Adversarial Audio Attacks.

Jason Henry, Mehmet Ergezer, Marko Orescanin

Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021

2020

Reducing Artifacts in GAN Audio Synthesis.

Nathan Thiem, Marko Orescanin, James Bret Michael

Proceedings of the 19th IEEE International Conference on Machine Learning and Applications, 2020

2010

Complex shear modulus reconstruction using ultrasound shear-wave imaging

Marko Orescanin

PhD thesis, 2010