no code implementations • 7 Jun 2023 • Suraj Bijjahalli, Oscar Pizarro, Stefan B. Williams
We evaluate the precision-recall tradeoff and demonstrate that by choosing an appropriate latent dimensionality and threshold, we are able to achieve an average precision of 0. 64 on unlabelled datasets.
1 code implementation • 20 Mar 2023 • Heather Doig, Oscar Pizarro, Stefan B. Williams
We adapt the SymmNet state-of-the-art Unsupervised Domain Adaptation method with an efficient bilinear pooling layer and image scaling to normalise spatial resolution, and show improved classification accuracy.
no code implementations • 13 Aug 2021 • Takaki Yamada, Adam Prügel-Bennett, Stefan B. Williams, Oscar Pizarro, Blair Thornton
We demonstrate how the latent representations generated by GeoCLR can be used to efficiently guide human annotation efforts, where the semi-supervised framework improves classification accuracy by an average of 10. 2% compared to the state-of-the-art SimCLR using the same CNN and equivalent number of human annotations for training.
no code implementations • 25 May 2021 • Jackson Shields, Oscar Pizarro, Stefan B. Williams
This research proposes methods for planning initial AUV surveys that efficiently explore a feature space representation of the bathymetry, in order to sample from a diverse set of bathymetric terrain.
no code implementations • 20 Jun 2020 • Jackson Shields, Oscar Pizarro, Stefan B. Williams
One such application is in benthic habitat mapping where these vehicles collect seafloor imagery that complements broadscale bathymetric data collected using sonar.
no code implementations • 27 Oct 2017 • Eric L. Ferguson, Stefan B. Williams, Craig T. Jin
The propagation of sound in a shallow water environment is characterized by boundary reflections from the sea surface and sea floor.
no code implementations • CVPR 2013 • Donald G. Dansereau, Oscar Pizarro, Stefan B. Williams
Results include calibration of a commercially available camera using three calibration grid sizes over five datasets.