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While at SRI International, Duda and Peter E. Hart were the authors of "Pattern Classification and Scene Analysis", originally published in 1973. This classic text is a widely cited reference, and the first edition was in print for over 25 years until being superseded by the second edition in 2000. [2] Duda is an IEEE Fellow and a AAAI Fellow. [3]
The Kernel-based Hough transform uses the same (,) parameterization proposed by Duda and Hart but operates on clusters of approximately collinear pixels. For each cluster, votes are cast using an oriented elliptical-Gaussian kernel that models the uncertainty associated with the best-fitting line with respect to the corresponding cluster.
The algorithm is widely used in robotics [4] to perform simplification and denoising of range data acquired by a rotating range scanner; in this field it is known as the split-and-merge algorithm and is attributed to Duda and Hart. [5]
Peter E. Hart (born 1941 [2]) is an American computer scientist and entrepreneur. He was chairman and president of Ricoh Innovations, which he founded in 1997.He made significant contributions in the field of computer science in a series of widely cited publications from the years 1967 to 1975 while associated with the Artificial Intelligence Center of SRI International, a laboratory where he ...
The method described in Duda et al. (2001) §3.8.3 projects the multivariate signal down to an M−1 dimensional space where M is the number of categories. MDA is useful because most classifiers are strongly affected by the curse of dimensionality .
Interest related to pattern recognition continued into the 1970s, as described by Duda and Hart in 1973. [16] In 1981 a report was given on using teaching strategies so that an artificial neural network learns to recognize 40 characters (26 letters, 10 digits, and 4 special symbols) from a computer terminal. [17]
Nationalist Duda, whose term in office expires in 2025, was one of Trump's preferred international partners during his presidency. The Polish president's top aide has said they remain in contact.
The Dunn index (DI) (introduced by J. C. Dunn in 1974) is a metric for evaluating clustering algorithms. [1] [2] This is part of a group of validity indices including the Davies–Bouldin index or Silhouette index, in that it is an internal evaluation scheme, where the result is based on the clustered data itself.