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Laser scanner intensity calibration based on artificial neural networks | IEEE Conference Publication | IEEE Xplore

Laser scanner intensity calibration based on artificial neural networks


Abstract:

In this study, we propose a method to calibrate the laser pulse return intensity of a Terrestrial Laser Scanner (TLS) based on Artificial Neural Networks. The laser pulse...Show More

Abstract:

In this study, we propose a method to calibrate the laser pulse return intensity of a Terrestrial Laser Scanner (TLS) based on Artificial Neural Networks. The laser pulse return intensity has an important rule on rocks types' classification when using Digital Outcrops Models (DOM) and has been the focus of much research by the geological community as it helps the geological interpretation in outcrops. In our experiment, we used a TLS Ilris 3D model with a wavelength of 1,535 nm. Our method has shown good efficiency for the calibration of the laser pulse return intensity, demonstrating a strong applicability for classification studies of rock types on Digital Outcrops Models.
Date of Conference: 23-28 July 2017
Date Added to IEEE Xplore: 04 December 2017
ISBN Information:
Electronic ISSN: 2153-7003
Conference Location: Fort Worth, TX, USA

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