Nonparametric analysis of LANDSAT maps using neural nets and parallel computers

Yehuda Salu; James C. Tilton

doi:10.1117/12.58067

1 April 1992 Nonparametric analysis of LANDSAT maps using neural nets and parallel computers

Yehuda Salu, James C. Tilton

Proceedings Volume 1623, The 20th AIPR Workshop: Computer Vision Applications: Meeting the Challenges; (1992) https://doi.org/10.1117/12.58067
Event: The 20th AIPR Workshop, 1991, McLean, VA, United States

Abstract

Nearest neighbor approaches and a new neural network, the Binary Diamond, are used for the classification of images of ground pixels obtained by LANDSAT satellite. The performances are evaluated by comparing classifications of a scene in the vicinity of Washington DC. The problem of optimal selection of categories is addressed as a step in the classification process.

Citation Download Citation

Yehuda Salu and James C. Tilton "Nonparametric analysis of LANDSAT maps using neural nets and parallel computers", Proc. SPIE 1623, The 20th AIPR Workshop: Computer Vision Applications: Meeting the Challenges, (1 April 1992); https://doi.org/10.1117/12.58067

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