Dana H. Ballard

From Wikipedia, the free encyclopedia
Jump to: navigation, search

Dana Harry Ballard (born 1946) is a professor of computer science currently at the University of Texas at Austin and formerly with the University of Rochester.[1]

Ballard received his Ph.D. from the University of California, Irvine. He has done research in artificial intelligence and human cognition and perception with a focus on the human visual system. In 1982, with Christopher M. Brown he authored a pioneering textbook in the field of computer vision, titled Computer Vision.[2] He also popularized the use of the generalised hough transform in computer vision in his paper "Generalizing the Hough Transform to Detect Arbitrary Shapes." [3] He is also known as a proponent of active vision techniques for computer vision systems [4] as well as approaches to understanding human vision.[5] His textbook titled "An Introduction to Natural Computation" (1997). It combines introductory material on varied subjects relevant to computing in the brain, such as neural networks, reinforcement learning, and genetic learning.[6] His most recent book, "Brain Computation as Hierarchical Abstraction," describes a multilevel approach to understanding neural computation.[7]

References[edit]

  1. ^ Personal Website
  2. ^ D.H. Ballard, C.M. Brown, Computer Vision, Prentice Hall, 1982
  3. ^ D.H. Ballard, "Generalizing the Hough Transform to Detect Arbitrary Shapes", Pattern Recognition, Vol.13, No.2, p.111-122, 1981
  4. ^ Ballard, D.H., "Animate vision," Artificial Intelligence Journal 48, 57-86, 1991
  5. ^ Ballard, D. H. and Hayhoe, M. M.(2009) Modeling the role of task in the control of gaze, Visual Cognition, 17, 1185-1204
  6. ^ Ballard (1997). An Introduction to Natural Computation. Cambridge, Massachusetts: MIT Press. 
  7. ^ Ballard (2015). Brain Computation as Hierarchical Abstraction. Cambridge, Massachusetts: MIT Press. 

Further reading[edit]