Browsing Cognitive & Neural Systems by Author "Martens, Siegfried"

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Browsing Cognitive & Neural Systems by Author "Martens, Siegfried"

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  • Carpenter, Gail; Martens, Siegfried; Mingolla, Ennio; Ogas, Ogi; Sai, Chaitanya (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2004-10)
    Ongoing research at Boston University has produced computational models of biological vision and learning that embody a growing corpus of scientific data and predictions. Vision models perform long-range grouping and ...
  • Martens, Siegfried (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2005-05)
  • 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. ...
  • Martens, Siegfried; Gaudiano, Paolo; Carpenter, Gail (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1998-03)
    The raw sensory input available to a mobile robot suffers from a variety of shortcomings. Sensor fusion can yield a percept more veridical than is available from any single sensor input. In this project, the fuzzy ARTMAP ...
  • Carpenter, Gail; Gopal, Sucharita; Macomber, Scott; Martens, Siegfried; Woodcock, Curtis (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1997-08)
    While most forest maps identify only the dominant vegetation class in delineated stands, individual stands are often better characterized by a mix of vegetation types. Many land management applications, including wildlife ...
  • Martens, Siegfried; Carpenter, Gail A.; Gaudiano, Paolo (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1998-08)
    An ARTMAP neural network is used to integrate visual information and ultrasonic sensory information on a B 14 mobile robot. Training samples for the neural network are acquired without human intervention. Sensory snapshots ...
  • 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 ...
  • Carpenter, Gail; Martens, Siegfried (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2005-01)
    Classifying terrain or objects may require the resolution of conflicting information from sensors working at different times, locations, and scales, and from users with different goals and situations. Current fusion methods ...
  • 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 ...

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