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20162026
most citedRecurrent neural circuits for contour detection

17 citations · 48 across the 21 of their papers we have counts for

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Showing 2018Show all

5 papers · 1 filter

cs.CV2018

Robust neural circuit reconstruction from serial electron microscopy with convolutional recurrent networks

Drew Linsley, Junkyung Kim, David Berson +1

Recent successes in deep learning have started to impact neuroscience. Of particular significance are claims that current segmentation algorithms achieve "super-human" accuracy in…

cs.CV2018

Robust pose tracking with a joint model of appearance and shape

Yuliang Guo, Lakshmi Narasimhan Govindarajan, Benjamin Kimia +1

We present a novel approach for estimating the 2D pose of an articulated object with an application to automated video analysis of small laboratory animals. We have found that defo…

cs.CV2018

Learning what and where to attend

Drew Linsley, Dan Shiebler, Sven Eberhardt +1

Most recent gains in visual recognition have originated from the inclusion of attention mechanisms in deep convolutional networks (DCNs). Because these networks are optimized for o…

cs.CV2018

Learning long-range spatial dependencies with horizontal gated-recurrent units

Drew Linsley, Junkyung Kim, Vijay Veerabadran +1

Progress in deep learning has spawned great successes in many engineering applications. As a prime example, convolutional neural networks, a type of feedforward neural networks, ar…

cs.CV2018

Same-different problems strain convolutional neural networks

Matthew Ricci, Junkyung Kim, Thomas Serre

The robust and efficient recognition of visual relations in images is a hallmark of biological vision. We argue that, despite recent progress in visual recognition, modern machine…