Andrew Spicer Bak

According to our database, Andrew Spicer Bak authored at least 7 papers between 2020 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2023

Automated Extraction of a Depth-Defined Wave Runup Time Series From Lidar Data Using Deep Learning.

Adam Collins, Annika O'Dea, Katherine L. Brodie, Andrew Spicer Bak, Tyler J. Hesser, Nicholas J. Spore, Matthew W. Farthing

IEEE Trans. Geosci. Remote. Sens., 2023

2022

CoastalImageLib: An open- source Python package for creating common coastal image products.

Maile P. McCann, Dylan Anderson, Christopher R. Sherwood, Brittany L. Bruder, Andrew Spicer Bak, Katherine L. Brodie

SoftwareX, December, 2022

Coastal Topo-Bathymetry from a Single-Pass Satellite Video: Insights in Space-Videos for Coastal Monitoring at Duck Beach (NC, USA).

Rafael Almar, Erwin W. J. Bergsma, Katherine L. Brodie, Andrew Spicer Bak, Stephanie Artigues, Solange Lemai-Chenevier, Guillaume Cesbron, Jean-Marc Delvit

Remote. Sens., 2022

2021

Development of a Fully Convolutional Neural Network to Derive Surf-Zone Bathymetry from Close-Range Imagery of Waves in Duck, NC.

Adam Collins, Matthew P. Geheran, Tyler J. Hesser, Andrew Spicer Bak, Katherine L. Brodie, Matthew W. Farthing

Remote. Sens., 2021

Quantifying Optically Derived Two-Dimensional Wave-Averaged Currents in the Surf Zone.

Dylan Anderson, Andrew Spicer Bak, Katherine L. Brodie, Nicholas Cohn, Robert A. Holman, John Stanley

Remote. Sens., 2021

2020

Bathymetric Inversion and Uncertainty Estimation from Synthetic Surf-Zone Imagery with Machine Learning.

Adam Collins, Katherine L. Brodie, Andrew Spicer Bak, Tyler J. Hesser, Matthew W. Farthing, Jonghyun Lee, Joseph W. Long

Remote. Sens., 2020

A 2D Fully Convolutional Neural Network for Nearshore And Surf-Zone Bathymetry Inversion from Synthetic Imagery of Surf-Zone using the Model Celeris.

Adam Collins, Katherine L. Brodie, Andrew Spicer Bak, Tyler J. Hesser, Matthew W. Farthing, Douglas W. Gamble, Joseph W. Long

Proceedings of the AAAI 2020 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 23rd - to, 2020