›Deep Learning for Photogrammetric Analysis and Remote Sensing
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).Tweets by spaceagenda