117 citations · 138 across the 6 of their papers we have counts for
6 papers
A Contrastive Learning Approach to Auroral Identification and Classification
Jeremiah W. Johnson, Swathi Hari, Donald Hampton +2
Unsupervised learning algorithms are beginning to achieve accuracies comparable to their supervised counterparts on benchmark computer vision tasks, but their utility for practical…
Detecting Invasive Ductal Carcinoma with Semi-Supervised Conditional GANs
Jeremiah W. Johnson
Invasive ductal carcinoma (IDC) comprises nearly 80% of all breast cancers. The detection of IDC is a necessary preprocessing step in determining the aggressiveness of the cancer,…
Structured Prediction using cGANs with Fusion Discriminator
Faisal Mahmood, Wenhao Xu, Nicholas J. Durr +2
We propose the fusion discriminator, a single unified framework for incorporating conditional information into a generative adversarial network (GAN) for a variety of distinct stru…
Subspace Match Probably Does Not Accurately Assess the Similarity of Learned Representations
Jeremiah Johnson
Learning informative representations of data is one of the primary goals of deep learning, but there is still little understanding as to what representations a neural network actua…
Adapting Mask-RCNN for Automatic Nucleus Segmentation
Jeremiah W. Johnson
Automatic segmentation of microscopy images is an important task in medical image processing and analysis. Nucleus detection is an important example of this task. Mask-RCNN is a re…
Neural Style Representations and the Large-Scale Classification of Artistic Style
Jeremiah Johnson
The artistic style of a painting is a subtle aesthetic judgment used by art historians for grouping and classifying artwork. The recently introduced `neural-style' algorithm substa…