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Journal ArticleDOI

Pattern Classification and Scene Analysis.

Ulf Grenander, +2 more
- 01 Sep 1974 - 
- Vol. 69, Iss: 347, pp 829
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This article is published in Journal of the American Statistical Association.The article was published on 1974-09-01. It has received 14948 citations till now.

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An algorithm for finding nearest neighbours in (approximately) constant average time

TL;DR: A new algorithm is proposed which finds the Nearest Neighbour of a given sample in approximately constant average time complexity, independent of the data set size, thus being of general use in many present applications of Pattern Recognition.
Journal ArticleDOI

Estimating foliage nitrogen concentration from HYMAP data using continuum, removal analysis

TL;DR: In this paper, the authors used the neural network method to estimate foliar biochemical concentrations from remote sensing data of eucalypt tree canopies, which are more complex than are spectra from many coniferous canyons and much more complex from dried ground leaves.
Proceedings ArticleDOI

Image-based skin color and texture analysis/synthesis by extracting hemoglobin and melanin information in the skin

TL;DR: A technique to synthesize the change of texture in pigment due to aging or the application of cosmetics is proposed, which could realistically change the skin color and texture of a 50 year-old woman to that of a 20 year- old woman.
Journal ArticleDOI

A fully decentralized multi-sensor system for tracking and surveillance

TL;DR: This article describes a multisensor surveillance system that achieves a high degree of survivability by employing a decentralized sensing architecture (Durrant-Whyte, Rao, and Hu 1990), and develops the algorithm to ensure that internodal commu nication is minimized and can take place without any prior synchronization between nodes.
Journal ArticleDOI

Measures of acutance and shape for classification of breast tumors

TL;DR: A region-based measure of image edge profile acutance is proposed which characterizes the transition in density of a region of interest (ROI) along normals to the ROI at every boundary pixel and indicates the importance of including lesion edge definition with shape information for classification of tumors.