34 citations · 51 across the 5 of their papers we have counts for
5 papers
Icon: An Interactive Approach to Train Deep Neural Networks for Segmentation of Neuronal Structures
Felix Gonda, Verena Kaynig, Ray Thouis +4
We present an interactive approach to train a deep neural network pixel classifier for the segmentation of neuronal structures. An interactive training scheme reduces the extremely…
Enforcing Label and Intensity Consistency for IR Target Detection
Toufiq Parag
This study formulates the IR target detection as a binary classification problem of each pixel. Each pixel is associated with a label which indicates whether it is a target or back…
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…