Philipe Ambrozio Dias R&D Associate in Computer Vision and Machine Learning Contact 865.341.2187 | AMBROZIODIAP@ORNL.GOV All Publications Interactive Rotated Object Detection for Novel Class Detection in Remotely Sensed Imagery OReole-FM: successes and challenges toward billion-parameter foundation models for high-resolution satellite imagery Inferring building height from footprint morphology data Introducing SpaceNet 9 - Cross-Modal Satellite Imagery Registration for Natural Disaster Responses Conditional Experts for Improved Building Damage Assessment Across Satellite Imagery View Angles Towards Diverse and Representative Global Pretraining Datasets for Remote Sensing Foundation Models... Pretraining Billion-Scale Geospatial Foundational Models on Frontier Benchmarking and end-to-end considerations for GeoAI-enabled decision making Chapter "GeoAI for Humanitarian Assistance" in Book "Handbook of Geospatial Artificial Intelligence" Scaling Automatic Vector Data Alignment to Satellite Imagery An Agenda for Multimodal Foundation Models for Earth Observation Towards Geospatial Knowledge Graph Infused Neuro-Symbolic AI for Remote Sensing Scene Understanding TOWARDS RAPID RESPONSE UPDATES OF POPULATIONS AT RISK... Post-Invasion Damage Assessment: Ukraine’s Crop Storage Infrastructure Semi-automated Design of Artificial Intelligence Earth Science Models Embedding Ethics and Trustworthiness for Sustainable AI in Earth Sciences: Where Do We Begin? Model Assumptions and Data Characteristics: Impacts on Domain Adaptation in Building Segmentation Key Links Curriculum Vitae Organizations National Security Sciences Directorate Geospatial Science and Human Security Division Geographic Data Science Section GeoAI Group
