Home Posters P2.47s Interpretable Machine Learning for the Early Smoke Wild-fire Detection P2.47s Interpretable Machine Learning for the Early Smoke Wild-fire Detection Advanced Satellite Systems Sensors & Intelligence Xiongren Chen, University of South Australia This project focuses on developing interpretable models for early smoke wild-fire detection from satellite images. Download Related Posters Advanced Satellite Systems Sensors & Intelligence Sai Vallapureddy, RMIT University P2.16s A Machine Learning Based Solution for Space Situational Awareness and Space Sustainability Advanced Satellite Systems Sensors & Intelligence David Shorten, The University of Adelaide P2.11 Trusted AI Frameworks for Change and Anomaly Detection in Observed ISR This project seeks to automate the identification of higher order... Advanced Satellite Systems Sensors & Intelligence Stefan Peters, University of South Australia P2.38 Small satellite energy-efficient on-board AI processing of hyperspectral imagery for early fire-smoke detection This research aims to provide a solution for energy-efficient...