Biography
Prof. Xiran Zhou
Prof. Xiran Zhou
China University of Mining and Technology, China
Title: Human-level landscape scene recognition with domain knowledge and remote sensing data
Abstract: 
Frequently-updated remote sensing image provides a potential to support large-scale landscape, and reinforce researchers’ competence in understanding, estimating and predicting the influences of natural forces and artificial activities. Recently, the rapid progress of deep learning approaches provides a big possibility of extracting high-level abstract features to characterize the complicated landscape scenes. However, the landscape categories derived from remote sensing images might be insufficient to predict the functionality and organization of different land parcels. For example, the state-of-the-art deep learning approaches can help people recognize different types of objects such as roads, buildings, trees in a variety of residential communities. However, the human-level results like “rich residential community and poor residential community” are challenging for these deep learning approaches. The integration of domain knowledge and the representation of remote sensing data might be an appropriate solution to deal with this challenge. This speech reports the proposed methodological framework to identify human-level landscape scene with features derived from remote sensing data and domain knowledge that landscape scene covers.
Biography: 
Xiran Zhou was born in Kunming Yunnan Province, China. He received the M.S. degree in from the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing at Wuhan University, and the Ph.D. degree from Arizona State University, US.
He is currently a Lecturer at China University of Mining and Technology, Xuzhou, China. His research interests in the areas of: geospatial artificial intelligence, remote sensing image interpretation, spatial data analysis, and data mining. He has over 20 publications in these areas. His current research focus covers landscape scene understanding with remote sensing data, and environmental big remote sensing data.
He is now serving as the editorial board member of International Journal of Geo-Spatial Knowledge and Intelligence, and the reviewer board member of Remote Sensing.