Deep Learning for SAR Image Analysis скачать в хорошем качестве

Deep Learning for SAR Image Analysis

This webinar is a part of the webinar series organised by the ISPRS WG III/3 (Active Microwave Remote Sensing) with the technical support of the ISPRS Student Consortium (ISPRS SC). Date: 11 June, 2025 Time: 12:00 - 13:00 (GMT+0) Title: Deep Learning for SAR Image Analysis Speaker: Michael Schmitt, University of the Bundeswehr Munich, Germany Moderator: Florence Tupin Abstract: In this talk, the combination of SAR-specific domain expertise and modern deep neural network machine learning architectures will be discussed. For that purpose, application examples such as the reconstruction of high-resolution urban height models from single SAR intensity images or the SAR-based estimation of vegetation indices, which are usually derived from multi-spectral optical data, will be addressed. Speaker's Bio: Michael Schmitt received his Dipl.-Ing. (Univ.) degree in geodesy and geoinformation, his Dr.-Ing. degree in remote sensing, and his habilitation in data fusion from the Technical University of Munich (TUM), Germany, in 2009, 2014, and 2018, respectively. Since 2021, he has been a Full Professor for Earth Observation at the Department of Aerospace Engineering of the University of the Bundeswehr Munich (UniBw M) in Neubiberg, Germany. He is a also a member of the Research Center SPACE and the Institute of Space Technology & Space Applications of UniBw M. His research focuses on technical aspects of Earth observation, in particular image analysis and machine learning applied to the extraction of information from multi-modal remote sensing observations. He is a co-chair of the Working Group ``Active Microwave Sensing'' of the International Society for Photogrammetry and Remote Sensing. More details: https://sc.isprs.org/resources/webinars/