Browsing Cognitive & Neural Systems by Subject "Adaptive resonance theory (ART)"

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Browsing Cognitive & Neural Systems by Subject "Adaptive resonance theory (ART)"

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  • ARTMAP Neural Networks for Information Fusion and Data Mining: Map Production and Target Recognition Methodologies
    Parsons, Olga; Carpenter, Gail (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2002-09)
    The Sensor Exploitation Group of MIT Lincoln Laboratory incorporated an early version of the ARTMAP neural network as the recognition engine of a hierarchical system for fusion and data mining of registered geospatial ...
  • Information Fusion and Hierarchical Knowledge Discovery by ARTMAP Neural Networks
    Carpenter, Gail; Martens, Siegfried; Ogas, Ogi; Rhodes, Bradley (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2003-12)
    Mapping novel terrain from sparse, complex data often requires the resolution of conflicting information from sensors working at different times, locations, and scales, and from experts with different goals and situations. ...
  • Self-Organizing Hierarchical Knowledge Discovery by an ARTMAP Image Fusion System
    Carpenter, Gail; Martens, Siegfried; Ogas, Ogi (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2004-01)
    Classifying novel terrain or objects front sparse, complex data may require the resolution of conflicting information from sensors working at different times, locations, and scales, and from sources with different goals ...
  • Self-Organizing Information Fusion and Hierarchical Knowledge Discovery: A New Framework Using Artmap Neural Networks
    Carpenter, Gail; Martens, Siegfried; Ogas, Ogi (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2004-12)
    Classifying novel terrain or objects from sparse, complex data may require the resolution of conflicting information from sensors woring at different times, locations, and scales, and from sources with different goals and ...
  • Self-Supervised ARTMAP
    Amis, Gregory P.; Carpenter, Gail A. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2009-05)
    Computational models of learning typically train on labeled input patterns (supervised learning), unlabeled input patterns (unsupervised learning), or a combination of the two (semisupervised learning). In each case input ...

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