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6-An Artificial Neural Network Approach for Land Cover Classification.

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dc.contributor.author Mohanty, K. K.
dc.date.accessioned 2022-03-08T20:27:02Z
dc.date.available 2022-03-08T20:27:02Z
dc.date.issued 1998
dc.identifier.uri http://117.252.14.250:8080/jspui/handle/123456789/6704
dc.description.abstract This paper presents a preliminary study on usage of Artificial Neural Network (ANN) for land cover classification using multispectral remotely sensed data. The ANN model used is a simple multi-layer perceptron trained through generalized delta learning rule. Performance of the ANN classifier has been assessed with reference to the conventional maximum likelihood (MXL) classifier. In the current study, it is found that the ANN classifier has a better classification accuracy than the MXL classifier. en_US
dc.language.iso en en_US
dc.publisher National Institute of Hydrology en_US
dc.subject Remote Sensing en_US
dc.subject GIS en_US
dc.subject Artificial Neural Network en_US
dc.title 6-An Artificial Neural Network Approach for Land Cover Classification. en_US
dc.type Technical Report en_US


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