AI RESEARCH
Toward Near-Real-Time Marine Oil Spill Detection in SAR Imagery using Quantum-Assisted SVM
arXiv CS.LG
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ArXi:2605.17217v1 Announce Type: cross Marine oil spills require rapid detection to mitigate severe ecological and economic damage. While satellite-based Synthetic Aperture Radar (SAR) provides essential all-weather monitoring, analyzing this data remains challenging. Deep learning models often require massive datasets and incur high latency. To address this, a pixel-wise quantum-assisted Vector Machine (QSVM) bagging ensemble is developed. Quantum annealing is leveraged to optimize the vectors of individual weak SVMs on small data subsets, which are then classically aggregated.