34 citations · 108 across the 9 of their papers we have counts for
6 papers · 1 filter
Automatic Neuron Type Identification by Neurite Localization in the Drosophila Medulla
Ting Zhao, Stephen M Plaza
Mapping the connectivity of neurons in the brain (i.e., connectomics) is a challenging problem due to both the number of connections in even the smallest organisms and the nanomete…
Identifying Synapses Using Deep and Wide Multiscale Recursive Networks
Gary B. Huang, Stephen Plaza
In this work, we propose a learning framework for identifying synapses using a deep and wide multi-scale recursive (DAWMR) network, previously considered in image segmentation appl…
Focused Proofreading: Efficiently Extracting Connectomes from Segmented EM Images
Stephen M. Plaza
Identifying complex neural circuitry from electron microscopic (EM) images may help unlock the mysteries of the brain. However, identifying this circuitry requires time-consuming,…
Annotating Synapses in Large EM Datasets
Stephen M. Plaza, Toufiq Parag, Gary B. Huang +3
Reconstructing neuronal circuits at the level of synapses is a central problem in neuroscience and becoming a focus of the emerging field of connectomics. To date, electron microsc…
Small Sample Learning of Superpixel Classifiers for EM Segmentation- Extended Version
Toufiq Parag, Stephen Plaza, Louis Scheffer
Pixel and superpixel classifiers have become essential tools for EM segmentation algorithms. Training these classifiers remains a major bottleneck primarily due to the requirement…
A Context-aware Delayed Agglomeration Framework for Electron Microscopy Segmentation
Toufiq Parag, Anirban Chakraborty, Stephen Plaza +1
Electron Microscopy (EM) image (or volume) segmentation has become significantly important in recent years as an instrument for connectomics. This paper proposes a novel agglomerat…