
MA
Mohanad Albughdadi
· 1 min read
ResearcharXiv cs.CV
MEOX: Modality-Conditioned Routing Before Fusion in a Compact Earth Observation Encoder
arXiv:2609.05351v3 Announce Type: replace
Abstract: Multimodal Earth Observation models often fuse radar and optical inputs early, limiting sensor-conditioned processing, or maintain separate sensor streams through the encoder, increasing computational cost. We present MEOX (Multimodal Earth Observation with eXperts), which delays fusion until after a shared mixture-of-experts block that processes Sentinel-2 and ascending and descending Sentinel-1 streams independently. Co-located patches are then fused with validity-aware weights into a single sequence processed by fourteen shared blocks, reducing the sequence length from 3N + 5 to N + 5 tokens for N patches. We pretrain the 2.939M-parameter encoder on 1.228M MMEarth64 samples using masked radar-optical reconstruction. Under the reported frozen-transfer protocols, MEOX reaches 90.56% average class accuracy on EuroSAT and 64.42% mean intersection over union (mIoU) on cashew segmentation, 2.26 and 5.02 points above the strongest reported cross-sensor mixture-of-experts (CSMoE) variants. Full-encoder adaptation increases BigEarthNet micro-average precision from 57.22% to 72.95%. In a controlled same-corpus test using synthetic random patch removal, masking 75% of Sentinel-2 patches reduces WorldCover mIoU from 30.45% to 26.53% when both Sentinel-1 streams remain available; with Sentinel-2 alone, mIoU falls to 13.81%. For identical zeroed optical patches, declaring them missing through the validity mechanism improves mIoU from 19.42% to 26.53%. These results characterize a compact route-then-fuse encoder that retains sensor-conditioned processing and uses complementary radar observations when optical inputs are incomplete.
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This story was published by arXiv cs.CV and written by Mohanad Albughdadi. SyncAI.news shows a preview; the complete article is on the publisher's site.
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