2007 - Fellow of John Simon Guggenheim Memorial Foundation
Communication, Cognitive neuroscience of visual object recognition, Cognitive psychology, Form perception and Perception are his primary areas of study. The various areas that Michael J. Tarr examines in his Communication study include Mental representation, Object, Artificial intelligence, Set and Psychophysics. His Artificial intelligence research integrates issues from Visual perception, Computer vision and Pattern recognition.
His work deals with themes such as Depth perception, Cognitive science and Categorization, which intersect with Cognitive neuroscience of visual object recognition. His Cognitive psychology research is multidisciplinary, incorporating perspectives in Fusiform gyrus, Face, Fusiform face area, Object and Occipital lobe. His Form perception study combines topics from a wide range of disciplines, such as Stimulus and Lateralization of brain function.
Michael J. Tarr mainly investigates Artificial intelligence, Cognitive neuroscience of visual object recognition, Cognitive psychology, Perception and Communication. His research integrates issues of Visual perception, Computer vision and Pattern recognition in his study of Artificial intelligence. Michael J. Tarr combines subjects such as Pattern recognition, Form perception, Visual cortex and Fusiform gyrus with his study of Cognitive neuroscience of visual object recognition.
His studies deal with areas such as Visual agnosia, Social psychology, Perceptual learning, Fusiform face area and Facial recognition system as well as Cognitive psychology. His Perception research incorporates elements of Stimulus, Cognitive science, Cognition and Categorization. The Communication study combines topics in areas such as Depth perception, Object, Psychophysics and Mental representation.
His primary scientific interests are in Artificial intelligence, Pattern recognition, Visual perception, Convolutional neural network and Visual cortex. His Artificial intelligence research includes elements of Machine learning and Computer vision. His Pattern recognition study combines topics in areas such as Correlation, Feature, Scaling and Magnetoencephalography.
His Visual perception study integrates concerns from other disciplines, such as Stimulus, Context and Neuroimaging. His biological study spans a wide range of topics, including Object, Representation and Affordance. His studies examine the connections between Cognitive neuroscience of visual object recognition and genetics, as well as such issues in Form perception, with regards to Communication.
His scientific interests lie mostly in Artificial intelligence, Pattern recognition, Visual perception, Cognitive neuroscience of visual object recognition and Form perception. Computational neuroscience is closely connected to Computer vision in his research, which is encompassed under the umbrella topic of Artificial intelligence. His Pattern recognition study incorporates themes from Machine learning, Neuroimaging, Visual cortex and Electroencephalography.
His Visual perception research is multidisciplinary, incorporating elements of Context, Stimulus, Vision science, Machine vision and Semantics. His Cognitive neuroscience of visual object recognition research includes themes of Cognitive psychology, Cognitive science and Communication. Michael J. Tarr interconnects Object model, Invariant and Object constancy in the investigation of issues within Communication.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Activation of the middle fusiform 'face area' increases with expertise in recognizing novel objects.
Isabel Gauthier;Michael J. Tarr;Adam W. Anderson;Pawel Skudlarski.
Nature Neuroscience (1999)
Becoming a “Greeble” Expert: Exploring Mechanisms for Face Recognition
Isabel Gauthier;Michael J. Tarr.
Vision Research (1997)
Mental rotation and orientation-dependence in shape recognition
Michael J Tarr;Steven Pinker.
Cognitive Psychology (1989)
The N170 occipito-temporal component is delayed and enhanced to inverted faces but not to inverted objects: an electrophysiological account of face-specific processes in the human brain
Bruno Rossion;Isabel Gauthier;Michael J Tarr;P Despland.
The Fusiform Face Area is Part of a Network that Processes Faces at the Individual Level
Isabel Gauthier;Michael J. Tarr;Jill Moylan;Pawel Skudlarski.
Journal of Cognitive Neuroscience (2000)
Early lateralization and orientation tuning for face, word, and object processing in the visual cortex
Bruno Rossion;Carrie A Joyce;Garrison W Cottrell;Michael J Tarr.
FFA: a flexible fusiform area for subordinate-level visual processing automatized by expertise
Michael J. Tarr;Isabel Gauthier.
Nature Neuroscience (2000)
Rotating objects to recognize them: A case study on the role of viewpoint dependency in the recognition of three-dimensional objects
Michael J. Tarr.
Psychonomic Bulletin & Review (1995)
Image-based object recognition in man, monkey and machine
Michael J. Tarr;Hienrich H. Bülthoff.
Is human object recognition better described by geon structural descriptions or by multiple views? Comment on Biederman and Gerhardstein (1993).
Michael J. Tarr;Heinrich H. Bülthoff.
Journal of Experimental Psychology: Human Perception and Performance (1995)
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: