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Bruno L.S.,Embrapa Instrumentacao Agropecuaria Brazil | Rodrigo B.P.,Embrapa Instrumentacao Agropecuaria Brazil | Lucio A.D.C.J.,Embrapa Instrumentacao Agropecuaria Brazil
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2016

This paper presents a system developed by an application of a neural network Multilayer Perceptron for drone acquired agricultural image segmentation. This application allows a supervised user training the classes that will posteriorly be interpreted by neural network. These classes will be generated manually with pre-selected attributes in the application. After the attribute selection a segmentation process is made to allow the relevant information extraction for different types of images, RGB or Hyperspectral. The application allows extracting the geographical coordinates from the image metadata, geo referencing all pixels on the image. In spite of excessive memory consume on hyperspectral images regions of interest, is possible to perform segmentation, using bands chosen by user that can be combined in different ways to obtain different results. © 2016 SPIE.

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