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G. Trudeau and Lowell, K., Detecting Coral Reef Presence Using ICESat-2 Data and Machine Learning Methods, Canadian Hydrographic Conference 2024. p. Saint John's, Newfoundland, Canada, 2024.PDF icon Trudeau_Lowell_CHC2024_Abstract.pdf (62.92 KB)
K. Lowell and Calder, B. R., Operational Performance of a Combined Density- and Clustering-based Approach to Extract Bathymetry Returns from LiDAR Point Clouds, International Journal of Applied Earth Observation and Geoinformation (Special Issue: Recent Advances in Geocomputation and GeoAI for Mapping), vol. 107. p. 102699, 2022.
K. Lowell and Calder, B. R., Extracting Shallow-water Bathymetry from Lidar Point Clouds Using Pulse Attribute Data: Merging Density-based and Machine Learning Approaches, Marine Geodesy, vol. 44(4) (DOI: Taylor and Francis, pp. 259-286, 2021.
K. Lowell, Calder, B. R., and Lyons, A. P., Measuring Shallow-water Bathymetric Signal Strength in Lidar Point Attribute Data Using Machine Learning, International Journal of Geographical Information Science, vol. 35(8) (DOI:10.1080/13658816.2020.1925790). Taylor and Francis, pp. 1592-1610, 2021.
J. Pierce, Rzhanov, Y., Lowell, K., and Dijkstra, J. A., Reducing Annotation Times: Semantic Segmentation of Coral Reef Survey Images, Global Oceans 2020. IEEE, U.S. Gulf Coast, Biloxi, MS, USA, pp. 1-9, 2020.
K. Lowell and Calder, B. R., Improving Extraction of Bathymetry from Lidar Using Machine Learning, 20th Annual Coastal Mapping & Charting Workshop of the Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX). p. Notre Dame, IN, 2019.