2023 - Research.com Computer Science in United States Leader Award
2017 - IEEE Frank Rosenblatt Award
2008 - Fellow of the American Educational Research Association
1994 - Fellow of the American Psychological Association (APA)
1991 - Neural Networks Pioneer Award, IEEE Computational Intelligence Society
1969 - Fellow of Alfred P. Sloan Foundation
His primary areas of investigation include Artificial intelligence, Artificial neural network, Neuroscience, Adaptive resonance theory and Cognition. He has researched Artificial intelligence in several fields, including Machine learning, Visual cortex, Computer vision and Pattern recognition. His study in Visual cortex is interdisciplinary in nature, drawing from both Cognitive neuroscience of visual object recognition, Visual perception, Perception, Cerebral cortex and Illusory contours.
His work carried out in the field of Artificial neural network brings together such families of science as Statistical hypothesis testing, Motor control, Control theory, Nonlinear system and Reinforcement. His studies examine the connections between Adaptive resonance theory and genetics, as well as such issues in Categorization, with regards to Amnesia. His research integrates issues of Cognitive psychology, Information processing, Cognitive science and Amygdala in his study of Cognition.
Stephen Grossberg mainly focuses on Artificial intelligence, Artificial neural network, Computer vision, Neuroscience and Visual cortex. His Artificial intelligence study combines topics from a wide range of disciplines, such as Visual perception, Perception and Pattern recognition. His Perception research includes themes of Cognitive science and Cognition.
Stephen Grossberg focuses mostly in the field of Artificial neural network, narrowing it down to topics relating to Speech recognition and, in certain cases, Speech perception. His work on Computer vision is being expanded to include thematically relevant topics such as Communication. His Visual cortex research is multidisciplinary, incorporating perspectives in Motion perception, Illusory contours, Neurophysiology and Receptive field.
Artificial intelligence, Computer vision, Perception, Cognitive psychology and Neuroscience are his primary areas of study. He has included themes like Concept learning and Visual cortex in his Artificial intelligence study. Stephen Grossberg interconnects Supervised learning and Invariant in the investigation of issues within Concept learning.
His Computer vision study integrates concerns from other disciplines, such as Depth perception and Communication. His work in the fields of Neuroscience, such as Hippocampal formation, Spatial memory and Temporal cortex, overlaps with other areas such as Acetylcholine. His work deals with themes such as Vigilance, Cognitive science, Cognition and Categorization, which intersect with Adaptive resonance theory.
Stephen Grossberg mainly investigates Artificial intelligence, Computer vision, Perception, Neuroscience and Eye movement. The various areas that Stephen Grossberg examines in his Artificial intelligence study include Machine learning, Visual cortex and Communication. His studies in Computer vision integrate themes in fields like Figure–ground and Depth perception.
His Perception research also works with subjects such as
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.
A massively parallel architecture for a self-organizing neural pattern recognition machine
Gail A Carpenter;Gail A Carpenter;Stephen Grossberg.
Graphical Models /graphical Models and Image Processing /computer Vision, Graphics, and Image Processing (1987)
Absolute stability of global pattern formation and parallel memory storage by competitive neural networks
M. A. Cohen;S. Grossberg.
systems man and cybernetics (1983)
Fuzzy ARTMAP: A neural network architecture for incremental supervised learning of analog multidimensional maps
G.A. Carpenter;S. Grossberg;N. Markuzon;J.H. Reynolds.
IEEE Transactions on Neural Networks (1992)
System for self-organization of stable category recognition codes for analog input patterns
Gail A. Carpenter;Stephen Grossberg.
Applied Optics (1987)
Fuzzy ART: Fast stable learning and categorization of analog patterns by an adaptive resonance system
Gail A. Carpenter;Stephen Grossberg;David B. Rosen.
Neural Networks (1991)
Adaptive pattern classification and universal recoding: I. Parallel development and coding of neural feature detectors
Biological Cybernetics (1976)
Nonlinear neural networks: Principles, mechanisms, and architectures
Neural Networks (1988)
The ART of adaptive pattern recognition by a self-organizing neural network
G.A. Carpenter;S. Grossberg.
IEEE Computer (1988)
How does a brain build a cognitive code
Psychological Review (1980)
Competitive Learning: From Interactive Activation to Adaptive Resonance
Cognitive Science (1987)
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: