Jay Hegdé

发表

Deep Synthesis of Realistic Medical Images: A Novel Tool in Clinical Research and Training

Evgeniy Bart, Jay Hegdé, J. Hegdé, 2018, Front. Neuroinform..

Reappraising the Functional Implications of the Primate Visual Anatomical Hierarchy

Jay Hegdé, Daniel J Felleman, J. Hegdé, 2007, The Neuroscientist : a review journal bringing neurobiology, neurology and psychiatry.

Invariant Recognition of Visual Objects: Some Emerging Computational Principles

Evgeniy Bart, Jay Hegdé, J. Hegdé, 2012, Front. Comput. Neurosci..

Editorial: Deep Learning in Biological, Computer, and Neuromorphic Systems

Evgeniy Bart, Jay Hegdé, J. Hegdé, 2019, Front. Comput. Neurosci..

How reliable is the pattern adaptation technique? A modeling study.

Jay Hegdé, J. Hegdé, 2009, Journal of neurophysiology.

Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Eugene Bart, Jay Hegdé, Daniel Kersten, 2012, Journal of visualized experiments : JoVE.

Deep learning can be used to train naïve, nonprofessional observers to detect diagnostic visual patterns of certain cancers in mammograms: a proof-of-principle study

Jay Hegdé, Jay Hegdé, 2020, Journal of medical imaging.

Invariant object recognition based on extended fragments

Evgeniy Bart, Jay Hegdé, J. Hegdé, 2012, Front. Comput. Neurosci..

Report Fragment-Based Learning of Visual Object Categories

Daniel Kersten, Evgeniy Bart, Jay Hegdé, 2008 .

Mental time travel sickness and a Bayesian remedy

Jay Hegdé, 2007 .

What the ‘Moonwalk’ Illusion Reveals about the Perception of Relative Depth from Motion

Evgeniy Bart, Jay Hegdé, Sarah Kromrey, 2011, PloS one.

Modeling the observed center-surround summation in macaque visual area V1

Jay Hegdé, D. J. Felleman, J. Hegdé, 2005, Neurocomputing.

Semantic descriptor ranking: a quantitative method for evaluating qualitative verbal reports of visual cognition in the laboratory or the clinic

Jay Hegdé, Matthew Maestri, Jeffrey Odel, 2014, Front. Psychol..