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Cross-Classification Clustering: An Efficient Multi-Object Tracking Technique for 3-D Instance Segmentation in Connectomics
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 object matching.
Toward Streaming Synapse Detection with Compositional ConvNets
Connectomics is an emerging field in neuroscience that aims to reconstruct the 3-dimensional morphology of neurons from electron microscopy (EM) images.
A Multi-Pass Approach to Large-Scale Connectomics
The field of connectomics faces unprecedented "big data" challenges.
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