# AI-Based On-Board Maritime Object Detection for Earth Observation Payload Data Reduction on Versal Embedded Hardware

arXiv: https://arxiv.org/abs/2610.12182 · HTML: https://mlsanity.com/paper/2610.12182/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 28 references that are in the map.
- First posted on arXiv 8 Oct 2026.

## Builds on (most cited first, 4 of 4)

- [YOLOX: Exceeding YOLO Series in 2021](https://mlsanity.com/paper/2107.08430/) (2021)
- [Advancing Earth Observation: A Survey on AI-Powered Image Processing in Satellites](https://mlsanity.com/paper/2501.12030/) (2025)
- [Rethinking Satellite Image Restoration for Onboard AI: A Lightweight Learning-Based Approach](https://mlsanity.com/paper/2604.12807/) (2026)
- [Embedded Bi-Temporal Building Damage Assessment for On-Board Data Reduction](https://mlsanity.com/paper/2609.37013/) (2026)

## Abstract (arXiv)

Very-high-resolution Earth-observation satellites acquire more data than they can store and downlink, while in maritime surveillance the vessels cover a tiny fraction of each scene. We study onboard vessel detection as a way to select what is downlinked, which reduces the data according to its content rather than coding every pixel; it is complementary to conventional onboard compression. The work follows three axes. (i) Data and algorithm: a controlled dataset is generated from 68 annotated Maxar scenes with 43 vessel classes, and a YOLOX-S detector is trained on it. (ii) Embedded deployment: the detector is quantized and deployed on the DPU of a Versal VC1902, with a limited loss of detection quality and a processing time of a few seconds per scene. (iii) Data reduction: we propose several downlink modes, from metadata only (box, class and score of each detection) to image crops around vessels, tiles holding detections, or the whole scene with a degraded background, and estimate from the measured detection errors the trade-off each offers between the vessels kept and the volume downlinked. On our dense harbor and coastal scenes, tiles keep 98% of the vessels with 29% of the scene volume, and crops 83% with 3%.