Satellite Workshop at IEEE ICIP 2025
Hyperspectral imaging has undergone remarkable advancements in recent years, shifting from labor-intensive and time-consuming processing methods to efficient, real-time analysis techniques. This workshop focuses on leveraging deep learning to tackle the unique challenges posed by hyperspectral imaging, including its inherent spectral complexity, high dimensionality, and the critical task of preserving spectral band integrity—an aspect often overlooked in conventional methods. The workshop will explore intelligent algorithms for automated data interpretation, advanced data fusion techniques for multi-source integration, and strategies to enhance spectral continuity in model outputs. Topics such as transfer learning, automated image classification, and segmentation will also be highlighted, showcasing their role in advancing hyperspectral imaging capabilities. This workshop aims to foster innovation and collaboration by bringing together leading researchers and practitioners advancing in hyperspectral imaging and applied AI applications across diverse sectors such as healthcare, environmental monitoring, agriculture, public safety, forensics sciences, and defense.
Topics
• Intelligent Algorithms for Automated Hyperspectral Data Analysis
• Optimizing Deep Learning Architectures for Hyperspectral Imaging
• Spectral Continuity Preservation in Deep Learning Models
• Data Fusion and Multi-Source Hyperspectral Analysis
• Transfer Learning for Hyperspectral Image Analysis
• Automated Hyperspectral Image Classification and Segmentation
Dr. Emanuela Marasco is an Assistant Professor in the Department of Information Sciences and Technology, affiliated with Computer Science at George Mason University. Her research expertise spans cybersecurity, biometrics, machine learning, deep learning, and computer vision. She has contributed to premier conferences such as IEEE WACV, IJCB, ICIP, and BigData and esteemed journals such as ACM Computing Surveys, Wiley, Springer, and PRL. Dr. Marasco has received two NSF EAGER Awards for research in hyperspectral biometrics and has actively collaborated on projects funded by NSF, DOJ.
Dr. Thirimachos Bourlai is a Professor at the University of Georgia’s School of Electrical and Computer Engineering, with joint appointments at the Savannah River National Laboratory and UGA’s Institute for Artificial Intelligence. He also holds adjunct faculty positions at West Virginia University in Computer Science and Ophthalmology. As the founder and director of the Multi-Spectral Imagery Lab, he spearheads cutting-edge research in hyperspectral and multispectral imaging technologies. Dr. Bourlai serves as the Series Editor for Advanced Sciences and Technologies for Security Applications, an Associate Editor for Pattern Recognition (Elsevier) and IET Electronics Letters, and a member of the Board of Directors for the Document Security Alliance. An accomplished scholar, he has authored extensive publications, including five books on biometrics and identity management.
- Raghavendra Ramachandra, Norwegian University of Science and Technology (Norway)
- Ketan Kotwal, IDIAP Research Institute (Switzerland)
- Bhargavi Janga, George Mason University (USA)
- Luismar Barbosa da Cruz Junior, University of São Paulo (Brazil)
- Alessio B. Chisari, University of Catania (Italy)