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Frontiers in Human Neuroscience|June 23, 2012
Object recognition in clutter: cortical responses depend on the type of learningJay Hegdé, Serena K Thompson, Mark Brady, et al.Journal of Visualized Experiments : Jove|November 15, 2012
Creating objects and object categories for studying perception and perceptual learningKarin Hauffen, Eugene Bart, Mark Brady, et al.The Journal of Neuroscience : the Official Journal of the Society for Neuroscience|November 12, 2010
A link between visual disambiguation and visual memoryJay Hegdé, Daniel KerstenCurrent Biology : CB|April 22, 2008
Fragment-based learning of visual object categoriesJay Hegdé, Evgeniy Bart, Daniel KerstenJournal of Vision|May 20, 2008
Preferential responses to occluded objects in the human visual cortexJay Hegdé, Fang Fang, Scott O Murray, et al.Progress in Neurobiology|November 3, 2007
Time course of visual perception: coarse-to-fine processing and beyondJay HegdéJournal of Medical Imaging (Bellingham, Wash.)|February 12, 2020
Deep learning can be used to train naïve, nonprofessional observers to detect diagnostic visual patterns of certain cancers in mammograms: a proof-of-principle studyJay HegdéJournal of Neurophysiology|June 26, 2009
How reliable is the pattern adaptation technique? A modeling studyJay HegdéFrontiers in Computational Neuroscience|September 1, 2012
Invariant object recognition based on extended fragmentsEvgeniy Bart, Jay HegdéPageof 10