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Browsing Cognitive & Neural Systems by Subject "Neural networks"

OpenBU

Browsing Cognitive & Neural Systems by Subject "Neural networks"

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  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-05)
    A neural network theory of :3-D vision, called FACADE Theory, is described. The theory proposes a solution of the classical figure-ground problem for biological vision. It does so by suggesting how boundary representations ...
  • Bullock, Daniel (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2003-09)
    Temporal structure in skilled, fluent action exists at several nested levels. At the largest scale considered here, short sequences of actions that are planned collectively in prefrontal cortex appear to be queued for ...
  • Carpenter, Gail; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-05)
    Adaptive Resonance Theory (ART) is a neural theory of human and primate information processing and of adaptive pattern recognition and prediction for technology. Biological applications to attentive learning of visual ...
  • Carpenter, Gail (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2000-09)
    Adaptive resonance is a theory of cognitive information processing which has been realized as a family of neural network models. In recent years, these models have evolved to incorporate new capabilities in the cognitive, ...
  • Grossberg, Stephen; Govindarajan, Krishna; Wyse, Lonce; Cohen, Michael (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2003-06)
    Multiple sound sources often contain harmonics that overlap and may be degraded by environmental noise. The auditory system is capable of teasing apart these sources into distinct mental objects, or streams. Such an "auditory ...
  • Carpenter, Gail A.; Grossberg, Stephen; Rosen, David (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1991-02)
    This article introduces ART 2-A, an efficient algorithm that emulates the self-organizing pattern recognition and hypothesis testing properties of the ART 2 neural network architecture, but at a speed two to three orders ...
  • Carpenter, Gail (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2000-03)
    ART (Adaptive Resonance Theory) neural networks for fast, stable learning and prediction have been applied in a variety of areas. Applications include airplane design and manufacturing, automatic target recognition, financial ...
  • Carpenter, Gail A.; Ross, William D. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1993-10)
    A new neural network architecture is introduced for the recognition of pattern classes after supervised and unsupervised learning. Applications include spatio-temporal image understanding and prediction and 3-D object ...
  • Shock, Byron; Carpenter, Gail; Gopal, Sucharita; Woodcock, Curtis (Boston University Computer Science Department, 2001-12)
    The ability to detect and monitor changes in land use is essential for assessment of the sustainability of development. In the next decade, NASA will gather high-resolution multi-spectral and multi-temporal data, which ...
  • Streilein, William W.; Gaudiano, Paolo; Carpenter, Gail A. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1998-05)
    ART (Adaptive Resonance Theory) neural networks for fast, stable learning and prediction have been applied in a variety of areas. Applications include automatic mapping from satellite remote sensing data, machine tool ...
  • Streilein, William W.; Gaudiano, Paolo; Carpenter, Gail A. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1998-05)
    ART (Adaptive Resonance Theory) neural networks for fast, stable learning and prediction have been applied in a variety of areas. Applications include automatic mapping from satellite remote sensing data, machine tool ...
  • Carpenter, Gail A.; Markuzon, Natalya (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1996-05)
    For complex database prediction problems such as medical diagnosis, the ARTMAP-IC neural network adds distributed prediction and category instance counting to the basic fuzzy ARTMAP system. For the ARTMAP match tracking ...
  • Ruda, Harald; Snorrason, Magnus (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1996-10)
    This paper documents an effort to design and implement a neural network-based, automatic classification system which dynamically constructs and trains a decision tree. The system is a combination of neural network and ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1999-01)
    The processes whereby our brains continue to learn about a changing world in a stable fashion throughout life are proposed to lead to conscious experiences. These processes include the learning of top-down expectations, ...
  • Gove, Alan; Grossberg, Stephen; Mingolla, Ennio (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-11)
    A neural network model is developed to explain how visual thalamocortical interactions give rise to boundary percepts such as illusory contours and surface percepts such as filled-in brightnesses. Top-down feedback ...
  • Campos, Marcos M.; Carpenter, Gail A. (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1999-01)
    This paper introduces CSOM, a continuous version of the Self-Organizing Map (SOM). The CSOM network generates maps similar to those created with the original SOM algorithm but, due to the continuous nature of the mapping, ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2000-09)
    How do our brains so effectively achieve adaptive behavior in a changing world? Evidence is reviewed that brains are organized into parallel processing streams with complementary properties. Hierarchical interactions within ...
  • Raizada, Rajeev; Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 2000-07)
    A detailed neural model is presented of how the laminar circuits of visual cortical areas V1 and V2 implement context-sensitive binding processes such as perceptual grouping and attention. The model proposes how specific ...
  • Pessoa, Luiz; Mingolla, Ennio; Neumann, Heiko (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1994-05)
    A neural network model of brightness perception is developed to account for a wide variety of data, including the classical phenomenon of Mach bands, low- and high-contrast missing fundamental, luminance staircases, and ...
  • Grossberg, Stephen (Boston University Center for Adaptive Systems and Department of Cognitive and Neural Systems, 1995-05)
    This article develops the FACADE theory of 3-D vision and figure-ground separation to explain data concerning how 2-D pictures give rise to 3-D percepts of occluding and occluded objects. These percepts include pop-out of ...

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