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T. Nishimura

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#machine learning Preprint Sep 2026

PoE-Fuse: Precision-Weighted Expert Fusion for Bi-Temporal Change Understanding

Bi-temporal change understanding, which localizes and characterizes what changed between two satellite images, is central to disaster response and environmental monitoring, spanning change detection, building localization, and damage assessment. Strong vision-language models address these tasks, but adapting them typic...

Haruki Watase, Shunya Nagashima, T. Nishimura · 0 citations

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