Satellite Image
Satellite image analysis is a rapidly evolving field focused on extracting meaningful information from Earth observation data for various applications. Current research emphasizes the use of deep learning, particularly convolutional neural networks (CNNs) and vision transformers (ViTs), for tasks such as object detection, segmentation, and classification, often incorporating techniques like attention mechanisms and transfer learning to improve efficiency and accuracy. These advancements are significantly impacting fields like environmental monitoring, urban planning, disaster response, and precision agriculture by enabling automated and large-scale analysis of geospatial data.
Papers
Splicing Detection and Localization In Satellite Imagery Using Conditional GANs
Emily R. Bartusiak, Sri Kalyan Yarlagadda, David Güera, Paolo Bestagini, Stefano Tubaro, Fengqing M. Zhu, Edward J. Delp
Understanding Urban Water Consumption using Remotely Sensed Data
Shaswat Mohanty, Anirudh Vijay, Shailesh Deshpande