3 citations · 5 across the 2 of their papers we have counts for
5 papers · 1 filter
The Challenge of Appearance-Free Object Tracking with Feedforward Neural Networks
Girik Malik, Drew Linsley, Thomas Serre +1
Nearly all models for object tracking with artificial neural networks depend on appearance features extracted from a "backbone" architecture, designed for object recognition. Indee…
Tracking Without Re-recognition in Humans and Machines
Drew Linsley, Girik Malik, Junkyung Kim +3
Imagine trying to track one particular fruitfly in a swarm of hundreds. Higher biological visual systems have evolved to track moving objects by relying on both appearance and moti…
Disentangling neural mechanisms for perceptual grouping
Junkyung Kim, Drew Linsley, Kalpit Thakkar +1
Forming perceptual groups and individuating objects in visual scenes is an essential step towards visual intelligence. This ability is thought to arise in the brain from computatio…
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…
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…