CLASSIFICATION OF EMPTY LAND AND SETTLEMENT PHOTOS USING SELF ORGANIZING MAP METHOD

Authors

  • Sunjana Department of Informatics, Faculty of Engineering, Widyatama University Cikutra No.204A, Bandung, West Java 40125 Author

Keywords:

Aerial photography, classification, SOM

Abstract

  Aerial Photos is the result of shooting an area of a certain height, in atmospheric space using a camera. For example shooting using airplanes, helicopters, blimps, drones or UAVs. Close review of aerial photography is to analyze land cover. One way to do the classification of images using the Artificial Neural Network method in aerial photography. ANN is a mathematical model, which imitates the workings of the nervous system of the human brain's nervous system. The way the nervous system of the human brain works is the transmission of signals from one neuron to thousands of other neurons. The Learning Model used is the Self Oganizing Map. SOM (Self Organizing Map), which is sometimes also known as Kohonen neural network system, is an artificial neural network model whose learning is unsupervised. This SOM learning system is grouping units according to a certain pattern with areas in the same class..

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Published

2022-01-30

How to Cite

Sunjana. (2022). CLASSIFICATION OF EMPTY LAND AND SETTLEMENT PHOTOS USING SELF ORGANIZING MAP METHOD. CENTRAL ASIA AND THE CAUCASUS, 23(1), 1086-1092. https://ca-c.org/CAC/index.php/cac/article/view/142

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