58 citations · 82 across the 4 of their papers we have counts for
4 papers
Image quality assessment for determining efficacy and limitations of Super-Resolution Convolutional Neural Network (SRCNN)
Chris M. Ward, Josh Harguess, Brendan Crabb +1
Traditional metrics for evaluating the efficacy of image processing techniques do not lend themselves to understanding the capabilities and limitations of modern image processing m…
Leveraging synthetic imagery for collision-at-sea avoidance
Chris M. Ward, Josh Harguess, Alexander G. Corelli
Maritime collisions involving multiple ships are considered rare, but in 2017 several United States Navy vessels were involved in fatal at-sea collisions that resulted in the death…
Ship classification from overhead imagery using synthetic data and domain adaptation
Chris M. Ward, Josh Harguess, Cameron Hilton
In this paper, we revisit the problem of classifying ships (maritime vessels) detected from overhead imagery. Despite the last decade of research on this very important and pertine…
MXNET-MPI: Embedding MPI parallelism in Parameter Server Task Model for scaling Deep Learning
Amith R Mamidala, Georgios Kollias, Chris Ward +1
Existing Deep Learning frameworks exclusively use either Parameter Server(PS) approach or MPI parallelism. In this paper, we discuss the drawbacks of such approaches and propose a…