The past three decades have seen the emergence of powerful new methods for image analysis and of novel architectural concepts for the design and construction of massively parallel machines, many motivated by the need to process images at high speeds. However, with some notable exceptions (the Image Understanding Architecture  for example, and the Connection Machine , to a lesser extent), research on architectures for image understanding has been driven more by classical models of image processing (essentially, image-to-image transformations and global feature extraction) than by the more powerful image representations and processing methods developed by the image understanding community.
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