ISPRS SC Webinar Series: Deep Learning for Photogrammetric Analysis and Remote Sensing [20 February 2020]

In today’s era of big data, deep learning techniques are becoming more vital to pursuing data intensive science. International space agencies are launching missions after missions and data are also collected using airborne and terrestrial remote sensing techniques at the regional and local levels. Exploring the potential and variety of applications from the vast quantity of remote sensing imagery calls for new tools that can automate and optimize the extraction of reliable and useful information and facilitate subsequent analyses.

The interest in deep learning in the fields of remote sensing and photogrammetry is increasing rapidly due to its capability to address the challenges in image processing and how it can harness the computing power of existing technologies.

The first webinar of the ISPRS SC Webinar Series for this year is on the basics of deep learning for photogrammetric analysis and remote sensing featuring Dr. Konrad Schindler of ETH Zurich. The lecture covers the basics of deep learning, including perceptron, training deep networks and examples on convolutional neural networks (CNN).  


About the Lecturer

Dr. Konrad Schindler is a professor at the Department of Civil, Environmental and Geomatic Engineering, Institute of Geodesy and Photogrammetry in ETH Zürich. He has completed his PhD in Computer Science in Graz University of Technology, Austria in 2003. Since then, he has published numerous papers on photogrammetry, remote sensing, computer vision and image interpretation. He has received several best presentation awards in various conferences and honours from international societies, including the U.V. Helava Award from ISPRS in 2012 and the Marr Prize Honourable Mention from the IEEE Computer Society in 2013.

For more information on Dr. Schindler, read our interview in the SpeCtrum, the official Newsletter of the ISPRS SC: