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SigLIP2 for aerial fire risk classification

Paper recorded by Signals 4 on 2026-10-02 in cs.CV. 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.CV · 计算机视觉 · first seen 2026-10-05

Abstract

We examine the transfer of a pretrained SigLIP2 image encoder to seven class fire risk classification from aerial imagery. We introduce a reproducible partition of the public FireRisk training mirror and an implementation that records data provenance, preprocessing and model selection. Two initial runs compare a frozen encoder probe with full model adaptation. On the validation partition, full ada

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#368 most recent of 756 cs.CV papers we have recorded · ↑ newer: FlowHMR: Physically Plausible Motion Capture from Video · ↓ older: ProAR: Learning Prospective Reasoning with Autoregressive Video Models
Cite this page: SigLIP2 for aerial fire risk classification: the #368 most recent of 756 cs.CV papers we have recorded (as of 2026-10-02). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/siglip2-for-aerial-fire-risk-classification.html
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