Synthetic Aperture Radar (SAR) Data Applications

End-to-End ATR Leveraging Deep Learning (M. Kreucher).- Change Detection in SAR Images using Deep Learning Methods (Bovolo).- Homography Augmented Momentum Contrastive Learning for SAR Image Retrieval (M. Rysz).- Synthetic Aperture Radar Image Based Navigation Using Siamese Neural Networks (Semenov).- A Comparison of Deep Neural Network Architectures in Aircraft Detection from SAR Imagery (L. Chen).- Machine Learning Methods for SAR Interference Mitigation (Huang).- Classification of SAR Images using Compact Convolutional Neural Networks (Ahishali).- Multi-frequency Polarimetric SAR Data Analysis for Crop Type Classification using Random Forest (Mandal).- Automatic Determination of Different Soil Types via Several Machine Learning Algorithms Employing Radarsat-2 SAR Image Polarization Coefficients (E. Acar).- Ocean and coastal area information retrieval using SAR polarimetry (A. Buono).

Maciej Rysz is currently an assistant professor at the Department of Information Systems & Analytics at the Farmer School of Business within Miami University. Prior to joining Miami University, he was a research assistant professor at the Industrial & Systems Engineering Department at the University of Florida and served as a postdoctoral research associate under the National Research Council of the National Academies. He received his Ph.D. in Industrial Engineering with emphasis on operations research from the University of Iowa in 2014. His research areas of interest include mathematical programming, machine learning, network science and encryption. 
Arsenios Tsokas currently works as an analyst for Citibank, N.A. He received his B.Sc. in Mathematics from the Aristotle University of Thessaloniki in 2014. He received his Ph.D. degree in Industrial & Systems Engineering from the University of Florida in 2021. He has a diverse background including data science, optimization, and machine learning. He has worked on various topics, such as data analysis with applications in medicine and network science with applications on network robustness.
Kathleen M Dipple is currently a research scientist with the US Air Force Research Lab (AFRL). A first-generation undergraduate student, she earned her bachelor's degree in Chemistry from Appalachian State University and received her Ph.D. from the Nanoscale Science program at the University of North Carolina at Charlotte. She completed her post-doctoral work holding a provisional patent in the Nature-Inspired Section at AFRL's Munitions Directorate through the National Research Council Associateship Program.
 Kaitlin Fair is a Systems Development Engineer working on guidance, navigation, and control technologies at the Air Force Life Cycle Management Center. Dr. Fair served as a Research Engineer and Team Lead at the Air Force Research Lab for ten years prior to