3 citations · 7 across the 10 of their papers we have counts for
4 papers · 2 filters
Enhancing Maritime Situational Awareness through End-to-End Onboard Raw Data Analysis
Roberto Del Prete, Manuel Salvoldi, Domenico Barretta +5
Satellite-based onboard data processing is crucial for time-sensitive applications requiring timely and efficient rapid response. Advances in edge artificial intelligence are shift…
Off to new Shores: A Dataset & Benchmark for (near-)coastal Flood Inundation Forecasting
Brandon Victor, Mathilde Letard, Peter Naylor +4
Floods are among the most common and devastating natural hazards, imposing immense costs on our society and economy due to their disastrous consequences. Recent progress in weather…
IMAFD: An Interpretable Multi-stage Approach to Flood Detection from time series Multispectral Data
Ziyang Zhang, Plamen Angelov, Dmitry Kangin +1
In this paper, we address two critical challenges in the domain of flood detection: the computational expense of large-scale time series change detection and the lack of interpreta…
Red Teaming Models for Hyperspectral Image Analysis Using Explainable AI
Vladimir Zaigrajew, Hubert Baniecki, Lukasz Tulczyjew +4
Remote sensing (RS) applications in the space domain demand machine learning (ML) models that are reliable, robust, and quality-assured, making red teaming a vital approach for ide…