3 citations · 3 across the 3 of their papers we have counts for
4 papers · 1 filter
Self-Supervised Learning of Synapse Types from EM Images
Aarav Shetty, Gary B Huang
Separating synapses into different classes based on their appearance in EM images has many applications in biology. Examples may include assigning a neurotransmitter to a particula…
Autoproof: Automated Segmentation Proofreading for Connectomics
Gary B Huang, William M Katz, Stuart Berg +1
Producing connectomes from electron microscopy (EM) images has historically required a great deal of human proofreading effort. This manual annotation cost is the current bottlenec…
Latent Feature Representation via Unsupervised Learning for Pattern Discovery in Massive Electron Microscopy Image Volumes
Gary B Huang, Huei-Fang Yang, Shin-ya Takemura +2
We propose a method to facilitate exploration and analysis of new large data sets. In particular, we give an unsupervised deep learning approach to learning a latent representation…
Fully-Automatic Synapse Prediction and Validation on a Large Data Set
Gary B. Huang, Louis K. Scheffer, Stephen M. Plaza
Extracting a connectome from an electron microscopy (EM) data set requires identification of neurons and determination of synapses between neurons. As manual extraction of this inf…