Manil Maskey of the Interagency Implementation and Advanced Concepts Team (IMPACT) and the Earth Science Branch, in collaboration with Saurabh Prasad from University of Houston, conducted a joint tutorial on Recent Advances in Deep Learning Models for Robust Ground Cover Classification from Multi-channel Geospatial Imagery at the Optical Sensors and Sensing Congress under the Hyperspectral Imaging and Sounding of the Environment track on 7/19/21. The tutorial covered theoretical concepts and evolution of artificial intelligence (specifically Deep Learning) and its application on satellite imagery. The primary goal of the tutorial was to educate the researchers working with multi-channel geospatial imagery on selecting proper deep learning techniques to address their research and application needs. The secondary goal of the tutorial was to demonstrate an end-to-end application of deep learning for multi-channel imagery.
