papers

Publications (5)

q-bio.QM2016

A Multi-Pass Approach to Large-Scale Connectomics

Yaron Meirovitch, Alexander Matveev, Hayk Saribekyan +8

The field of connectomics faces unprecedented "big data" challenges. To reconstruct neuronal connectivity, automated pixel-level segmentation is required for petabytes of streaming…

cs.CV2019

Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics

Yaron Meirovitch, Lu Mi, Hayk Saribekyan +3

Pixel-accurate tracking of objects is a key element in many computer vision applications, often solved by iterated individual object tracking or instance segmentation followed by o…

cs.CV2017

Toward Streaming Synapse Detection with Compositional ConvNets

Shibani Santurkar, David Budden, Alexander Matveev +4

Connectomics is an emerging field in neuroscience that aims to reconstruct the 3-dimensional morphology of neurons from electron microscopy (EM) images. Recent studies have success…

cs.DC2014

The LevelArray: A Fast, Practical Long-Lived Renaming Algorithm

Dan Alistarh, Justin Kopinsky, Alexander Matveev +1

The long-lived renaming problem appears in shared-memory systems where a set of threads need to register and deregister frequently from the computation, while concurrent operations…

cs.CV2017

Deep Tensor Convolution on Multicores

David Budden, Alexander Matveev, Shibani Santurkar +2

Deep convolutional neural networks (ConvNets) of 3-dimensional kernels allow joint modeling of spatiotemporal features. These networks have improved performance of video and volume…