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Author Title Type Year(Asc)
Accepted
Adriano, A., K. Scott, A., & Azad, N. Lashgarian. (Accepted). Extreme Gradient Boosting and Deep Learning Models for the Classification of Synthetic Space Debris Light Curves. In AMOS Advanced Maui Optical and Space Surveillance Technologies Conference.
de Loë, L., Xu, L., & K. Scott, A.. (Accepted). Fusing ice surface temperature with the AI4Arctic dataset for enhanced sea ice concentration estimation: A preliminary assessment. In IEEE Oceans 2024.
Kazemi, S., Azad, N. L., K Scott, A., Oqab, H. B., & Dietrich, G. B.. (Accepted). Satellite Collision Avoidance Maneuver Planning in Low Earth Orbit using Proximal Policy Optimization. In IEEE World Congress on Computational Intelligence. IEEE.
Patel, M., Xu, L., Chen, X., Scott, A., & Chen, Y.. (Accepted). Region-level labels in ice charts can produce pixel-level segmentation for sea ice types. In International Conference on Learning Representations (ICLR). May 2024.
Attiah, G., Pour, H. Kheyrollah, & K Scott, A.. (Accepted). Lake Surface Temperature Dataset in the North Slave Region Retrieved from Landsat Satellite Series - 1984 to 2021. Earth System Science Data.
2024
Chen, X., Patel, M., Cantu, F. Pena, Park, J., Turnes, J. Noa, Xu, L., K Scott, A., et al. (2024). MMSeaIce: Multi-task mapping of sea ice parameters from AI4Arctic sea ice challenge dataset. The Cryosphere. Retrieved from https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1297/
2023
Soleymani, A., & K Scott, A.. (2023). Arctic marginal ice zone interannual variability and change point detection using two definitions. Environmental Research Letters, 18(12), 124002. Retrieved from https://iopscience.iop.org/article/10.1088/1748-9326/ad0609
Chen, X., Patel, M., Xu, L., Chen, Y., K Scott, A., & Clausi, D. A.. (2023). Weakly supervised learning for sea ice concentration extraction using AI4Arctic sea ice challenge dataset. IEEE Geoscience and Remote Sensing Letters, 21. Retrieved from https://ieeexplore.ieee.org/document/10335753
Rusin, J., Lavergne, T., Doulgeris, A. Paul, & Scott, K. A.. (2023). Resolution enhanced sea ice concentration: A new algorithm applied to AMSR2 microwave radiometry data. Annals of Glaciology. Retrieved from https://www.cambridge.org/core/journals/annals-of-glaciology/article/resolution-enhanced-sea-ice-concentration-a-new-algorithm-applied-to-amsr2-microwave-radiometry-data/3F83D752D15933B4BE23E442CA5B9CEE
Chen, X., K Scott, A., Jiang, M., Fang, Y., Xu, L., & Clausi, D. A.. (2023). Sea ice classification with dual-polarized SAR imagery: a hierarchical pipeline. In First Workshop on Maritime Computer Vision (MaCVi). The Computer Vision Foundation. chen_sea_ice_classification_with_dual-polarized_sar_imagery_a_hierarchical_pipeline_wacvw_2023_paper.pdf
Soleymani, A., & K. Scott, A.. (2023). Passive microwave sea ice edge displacement error over the eastern Canadian Arctic 2013-2021. Canadian Journal of Remote Sensing.
Valencia, R., Chen, X., & K. Scott, A.. (2023). Predicting Sea Ice Concentration with Calibrated Uncertainty Quantification using Passive Microwave and Reanalysis Data: A Case Study in Baffin Bay. IEEE Transcations on Geoscience and Remote Sensing. sic_uncertainty_tgrs_paper_revision.pdf
Grace, A. P., Stastna, M., Lamb, K. G., & Scott, K. A.. (2023). Gravity currents in the cabbeling regime. Physical Review Fluids, 8, 014502. Retrieved from https://journals.aps.org/prfluids/abstract/10.1103/PhysRevFluids.8.014502?ft=1
2022
Asadi, N., Lamontagne, P., King, M., Richard, M., & Scott, K. A.. (2022). Probabilistic Spatio-temporal Seasonal Sea Ice Presence Forecastingusing Sequence-to-Sequence Learning and ERA5 data in the Hudson Bay region. The Cryosphere. probabilistic_sea_ice_forecasting_nrc.pdf
Chen, X., K Scott, A., Xu, L., Jiang, M., & Clausi, D. A.. (2022). Uncertainty-Incorporated Ice and Open WaterDetection on Dual-Polarized SAR Sea Ice Imagery. IEEE Transactions on Geoscience and Remote Sensing. uncertainty-incorporated_ice_and_open_water_detection_on_dual-polarized_sar_sea_ice_imagery.pdf
Saberi, N., Scott, K. A., & Duguay, C.. (2022). Incorporating aleatoric uncertainties of lake ice mapping in SARimagery using CNNs. Remote Sensing. Retrieved from https://www.mdpi.com/2072-4292/14/3/644
Grace, A., Stastna, M., Lamb, K. G., & Scott, K. A.. (2022). Numerical simulations of the three-dimensionalization of a shear flow in radiatively forced cold water below the density maximum. Physical Review Fluids. Retrieved from https://journals.aps.org/prfluids/accepted/1807eS60X0a11a02314214a6e1b4b7f1ad2cdd686
Tamber, M., Scott, K. A., & Pedersen, L. T.. (2022). Accounting for label errors when training a convolutional neural network to estimate sea ice concentration using operational ice charts. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. Retrieved from https://ieeexplore.ieee.org/document/9674865
Sola, D., & Scott, K. A.. (2022). Efficient Shallow Network for River Ice Segmentation. Remote Sensing. Retrieved from https://www.mdpi.com/2072-4292/14/10/2378
2021
Nagi, A. S., Kumar, D., Sola, D., & Scott, K. A.. (2021). UF: Effective Sea Ice Floe Segmentation Using End-to-End RES-UNET-CRF. Remote Sensing. Retrieved from https://www.mdpi.com/2072-4292/13/13/2460

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