Title: Adapted bucolic and farming region pattern classification using artificial neural networks for remote sensing images

Authors: P.S. Jagadeesh Kumar; Tracy Lin Huan

Addresses: Department of Earth Sciences (EARS), Dartmouth College, Hanover, New Hampshire, 03755, USA ' Department of Earth Sciences (EARS), Dartmouth College, Hanover, New Hampshire, 03755, USA

Abstract: This paper explicates the utilisation of multi-layer perceptron neural networks-based procedural for the classification of bucolic and farming regions of remotely sensed images. In this paper, spectral remote sensing images were apprehended in rural and agricultural taxonomy. Cumulative histograms, voronoi tessellation, spatial pixel matrix extorted from the geographical information system were used for the training of the dataset as endowment to the multi-layer perceptron neural networks. The obstinacy of image texture features using voronoi tessellation was prompted to be principal for aerial image pattern classification of bucolic and farming regions.

Keywords: agricultural region; cumulative histogram; geographical information system; multi-layer perceptron-based neural networks; pattern classification; remote sensing image; voronoi tessellation.

DOI: 10.1504/IJAIP.2023.130820

International Journal of Advanced Intelligence Paradigms, 2023 Vol.25 No.1/2, pp.163 - 184

Received: 18 Mar 2017
Accepted: 27 May 2018
Published online: 11 May 2023 *

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