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Sensitivity to Timing and Order in Human Visual Cortex.
(Center for Brains, Minds and Machines (CBMM), arXiv, 2014-04-25)
Visual recognition takes a small fraction of a second and relies on the cascade of signals along the ventral visual stream. Given the rapid path through multiple processing steps between photoreceptors and higher visual ...
A normalization model of visual search predicts single trial human fixations in an object search task.
(Center for Brains, Minds and Machines (CBMM), arXiv, 2014-04-25)
When searching for an object in a scene, how does the brain decide where to look next? Theories of visual search suggest the existence of a global attentional map, computed by integrating bottom-up visual information with ...
A role for recurrent processing in object completion: neurophysiological, psychophysical and computational evidence.
(Center for Brains, Minds and Machines (CBMM), arXiv, 2014-04-26)
Recognition of objects from partial information presents a significant challenge for theories of vision because it requires spatial integration and extrapolation from prior knowledge. We combined neurophysiological recordings ...
UNSUPERVISED LEARNING OF VISUAL STRUCTURE USING PREDICTIVE GENERATIVE NETWORKS
(Center for Brains, Minds and Machines (CBMM), arXiv, 2015-12-15)
The ability to predict future states of the environment is a central pillar of intelligence. At its core, effective prediction requires an internal model of the world and an understanding of the rules by which the world ...
On the Robustness of Convolutional Neural Networks to Internal Architecture and Weight Perturbations
(Center for Brains, Minds and Machines (CBMM), arXiv, 2017-04-03)
Deep convolutional neural networks are generally regarded as robust function approximators. So far, this intuition is based on perturbations to external stimuli such as the images to be classified. Here we explore the ...
Deep Predictive Coding Networks for Video Prediction and Unsupervised Learning
(Center for Brains, Minds and Machines (CBMM), arXiv, 2017-03-01)
While great strides have been made in using deep learning algorithms to solve supervised learning tasks, the problem of unsupervised learning—leveraging unlabeled examples to learn about the structure of a domain — remains ...
What am I searching for?
(Center for Brains, Minds and Machines (CBMM), arXiv.org, 2018-07-31)
Can we infer intentions and goals from a person's actions? As an example of this family of problems, we consider here whether it is possible to decipher what a person is searching for by decoding their eye movement behavior. ...
Spatiotemporal interpretation features in the recognition of dynamic images
(Center for Brains, Minds and Machines (CBMM), 2018-11-21)
Objects and their parts can be visually recognized and localized from purely spatial information in static images and also from purely temporal information as in the perception of biological motion. Cortical regions have ...