What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Perception
- Cognition
His main research concerns Perception, Communication, Cognitive neuroscience of visual object recognition, Artificial intelligence and Cognitive psychology.
His biological study spans a wide range of topics, including Cued speech, Word recognition, Stroop effect and Information processing.
His research integrates issues of Temporal cortex, Psychophysics, Visual cortex and Priming in his study of Communication.
His research in Cognitive neuroscience of visual object recognition intersects with topics in Depth perception, Curvature and Form perception.
His Artificial intelligence research is multidisciplinary, relying on both Object perception, Computer vision and Pattern recognition.
His Cognitive psychology research integrates issues from Visual perception, Dissociation, Cognition and Iconic memory.
His most cited work include:
- Recognition-by-Components: A Theory of Human Image Understanding. (4573 citations)
- Scene Perception" Detecting and Judging Objects Undergoing Relational Violations (834 citations)
- Dynamic binding in a neural network for shape recognition. (787 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Artificial intelligence, Communication, Pattern recognition, Cognitive neuroscience of visual object recognition and Cognitive psychology.
Irving Biederman has included themes like Form perception, Perception and Computer vision in his Artificial intelligence study.
His Communication research incorporates elements of Object, Psychophysics, Visual cortex and Priming.
His Pattern recognition research is multidisciplinary, incorporating elements of Metric and Contrast.
His work on 3D single-object recognition as part of general Cognitive neuroscience of visual object recognition research is often related to Geon, thus linking different fields of science.
He has researched Cognitive psychology in several fields, including Stimulus, Face, Social psychology and Cognition.
He most often published in these fields:
- Artificial intelligence (45.53%)
- Communication (27.24%)
- Pattern recognition (26.42%)
What were the highlights of his more recent work (between 2009-2020)?
- Artificial intelligence (45.53%)
- Pattern recognition (26.42%)
- Cognitive psychology (21.14%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Artificial intelligence, Pattern recognition, Cognitive psychology, Communication and Perception.
His Artificial intelligence research includes elements of Invariant and Computer vision.
His research investigates the connection with Pattern recognition and areas like Contrast which intersect with concerns in Fusiform face area.
His study in Communication is interdisciplinary in nature, drawing from both Occipital lobe, Object, Lateral occipital complex and Lateral occipital cortex.
His studies deal with areas such as Bold response, Blood-oxygen-level dependent and Functional magnetic resonance imaging as well as Perception.
His Cognitive neuroscience of visual object recognition research includes themes of Visual perception, Spatial relation and Fusiform gyrus.
Between 2009 and 2020, his most popular works were:
- Where Do Objects Become Scenes (71 citations)
- Loci of the release from fMRI adaptation for changes in facial expression, identity, and viewpoint. (53 citations)
- Cortical Representation of Medial Axis Structure (52 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Perception
- Cognition
Irving Biederman mainly investigates Cognitive psychology, Communication, Artificial intelligence, Pattern recognition and Perception.
His work deals with themes such as Basis, fMRI adaptation, Lateral occipital cortex, Object and Neural activity, which intersect with Communication.
In the subject of general Artificial intelligence, his work in Cognitive neuroscience of visual object recognition is often linked to Geon, thereby combining diverse domains of study.
His Cognitive neuroscience of visual object recognition research is classified as research in Computer vision.
His Pattern recognition research is multidisciplinary, incorporating perspectives in Receptive field, Face perception, Form perception, Invariant and Rendering.
His Perception study combines topics in areas such as Mathematical analysis, Lateral occipital complex, Facial recognition system and Blood-oxygen-level dependent, Functional magnetic resonance imaging.
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