55 citations · 197 across the 20 of their papers we have counts for
4 papers · 1 filter
Can VAEs Generate Novel Examples?
Alican Bozkurt, Babak Esmaeili, Dana H. Brooks +2
An implicit goal in works on deep generative models is that such models should be able to generate novel examples that were not previously seen in the training data. In this paper,…
Deep feature transfer between localization and segmentation tasks
Szu-Yeu Hu, Andrew Beers, Ken Chang +8
In this paper, we propose a new pre-training scheme for U-net based image segmentation. We first train the encoding arm as a localization network to predict the center of the targe…
Quantifying Uncertainty in Discrete-Continuous and Skewed Data with Bayesian Deep Learning
Thomas Vandal, Evan Kodra, Jennifer Dy +3
Deep Learning (DL) methods have been transforming computer vision with innovative adaptations to other domains including climate change. For DL to pervade Science and Engineering (…
A Multiresolution Convolutional Neural Network with Partial Label Training for Annotating Reflectance Confocal Microscopy Images of Skin
Alican Bozkurt, Kivanc Kose, Christi Alessi-Fox +4
We describe a new multiresolution "nested encoder-decoder" convolutional network architecture and use it to annotate morphological patterns in reflectance confocal microscopy (RCM)…