5 papers
A Unified Framework for Efficient Remote Sensing Visual Question Answering: Adapting Dual, Hybrid, and Encoder-Decoder Architectures
Timothy Agboada, Shikha Chandel, Yadav Raj Ghimire +1
Visual Question Answering (VQA) in the Remote Sensing (RS) domain presents unique challenges due to the high resolution, multi scale object distribution, and semantic complexity of…
Bridging Spatial And Frequency Views For Disaster Assessment: Benefits And Limitations
Shikha V. Chandel, Yadav Raj Ghimire, Timothy Agboada +1
Rapid assessment of building damage from satellite imagery is essential for effective disaster response and recovery. While most deep learning methods rely on spatial-domain featur…
Comparison of Deep Learning Frameworks For Rice Disease Mapping From UAV Multispectral Imaging
Yadav Raj Ghimire, Jagrati Talreja, Tewodros Syum Gebre +3
In this study, UAV multispectral imagery is used to segment the severity of bacterial leaf blight (BLB) in rice using convolutional neural networks (CNNs) and transformer-based mod…
Physics-Informed Machine Learning for Short-Term Flood Prediction
Tewodros Syum Gebre, Jagrati Talreja, Leila Hashemi-Beni
Accurate flood forecasting is essential for mitigating disaster risks and protecting communities. However, purely data-driven machine learning models often struggle in data-scarce…
Overcoming "Physics Shock" in Earth Observation A Heteroscedastic Uncertainty Framework for PINN-based Flood Inference
Tewodros Syum Gebre, Jagrati Talreja, Matilda Anokye +1
Rapid and accurate flood extent mapping from Remote Sensing data, such as Synthetic Aperture Radar (SAR), is critical for operational disaster response, but standard Deep Learning…