189 citations · 311 across the 19 of their papers we have counts for
6 papers · 1 filter
Weakly-Supervised Semantic Segmentation of Ships Using Thermal Imagery
Rushil Joshi, Ethan Adams, Matthew Ziemann +1
The United States coastline spans 95,471 miles; a distance that cannot be effectively patrolled or secured by manual human effort alone. Unmanned Aerial Vehicles (UAVs) equipped wi…
MetaDIP: Accelerating Deep Image Prior with Meta Learning
Kevin Zhang, Mingyang Xie, Maharshi Gor +3
Deep image prior (DIP) is a recently proposed technique for solving imaging inverse problems by fitting the reconstructed images to the output of an untrained convolutional neural…
Denoising Generalized Expectation-Consistent Approximation for MR Image Recovery
Saurav K. Shastri, Rizwan Ahmad, Christopher A. Metzler +1
To solve inverse problems, plug-and-play (PnP) methods replace the proximal step in a convex optimization algorithm with a call to an application-specific denoiser, often implement…
TurbuGAN: An Adversarial Learning Approach to Spatially-Varying Multiframe Blind Deconvolution with Applications to Imaging Through Turbulence
Brandon Yushan Feng, Mingyang Xie, Christopher A. Metzler
We present a self-supervised and self-calibrating multi-shot approach to imaging through atmospheric turbulence, called TurbuGAN. Our approach requires no paired training data, ada…
Expectation Consistent Plug-and-Play for MRI
Saurav K Shastri, Rizwan Ahmad, Christopher A Metzler +1
For image recovery problems, plug-and-play (PnP) methods have been developed that replace the proximal step in an optimization algorithm with a call to an application-specific deno…
Supervision by Denoising for Medical Image Segmentation
Sean I. Young, Adrian V. Dalca, Enzo Ferrante +4
Learning-based image reconstruction models, such as those based on the U-Net, require a large set of labeled images if good generalization is to be guaranteed. In some imaging doma…