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On-Board Anomaly Detection for Efficient Marine Environmental Monitoring

Paper recorded by Signals 4 on 2026-10-02 in cs.AI. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-02 on arXiv · recorded by Signals 4 on 2026-10-05

Category: cs.AI · 人工智能 · first seen 2026-10-05

Abstract

Marine ecosystems are impacted by various threats such as oil spills, algal blooms, and sediment floods, which disrupt habitats, wildlife, and human activities. Advances in satellite imagery and Artificial Intelligence (AI) have enhanced our capabilities for early detection and mitigation of such hazards. In this paper, we propose a marine event detection pipeline for Earth observation satellites

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#509 most recent of 1020 cs.AI papers we have recorded · ↑ newer: MRVQ: One Resident Index for Dimension- and Rate-Elastic Vector Search · ↓ older: Do Large Language Models Know Colombian Law? A Reliability Benchmark f
Cite this page: On-Board Anomaly Detection for Efficient Marine Environmental Monitoring: the #509 most recent of 1020 cs.AI papers we have recorded (as of 2026-10-02). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/on-board-anomaly-detection-for-efficient-marine-environmental-monitoring.html
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