Search Results for author: David Williams

Found 5 papers, 0 papers with code

Essential Metadata for 3D BRAIN Microscopy

no code implementations18 May 2021 Alexander J. Ropelewski, Megan A. Rizzo, Jason R. Swedlow, Jan Huisken, Pavel Osten, Neda Khanjani, Kurt Weiss, Vesselina Bakalov, Michelle Engle, Lauren Gridley, Michelle Krzyzanowski, Tom Madden, Deborah Maiese, Justin Waterfield, David Williams, Carol Hamilton, Wayne Huggins

Recent advances in fluorescence microscopy techniques and tissue clearing, labeling, and staining provide unprecedented opportunities to investigate brain structure and function.

Fool Me Once: Robust Selective Segmentation via Out-of-Distribution Detection with Contrastive Learning

no code implementations1 Mar 2021 David Williams, Matthew Gadd, Daniele De Martini, Paul Newman

In this work, we train a network to simultaneously perform segmentation and pixel-wise Out-of-Distribution (OoD) detection, such that the segmentation of unknown regions of scenes can be rejected.

Contrastive Learning Data Augmentation +3

Keep off the Grass: Permissible Driving Routes from Radar with Weak Audio Supervision

no code implementations11 May 2020 David Williams, Daniele De Martini, Matthew Gadd, Letizia Marchegiani, Paul Newman

Reliable outdoor deployment of mobile robots requires the robust identification of permissible driving routes in a given environment.

Coupling Rendering and Generative Adversarial Networks for Artificial SAS Image Generation

no code implementations13 Sep 2019 Albert Reed, Isaac Gerg, John McKay, Daniel Brown, David Williams, Suren Jayasuriya

Acquisition of Synthetic Aperture Sonar (SAS) datasets is bottlenecked by the costly deployment of SAS imaging systems, and even when data acquisition is possible, the data is often skewed towards containing barren seafloor rather than objects of interest.

Generative Adversarial Network Image Generation

Cannot find the paper you are looking for? You can Submit a new open access paper.