A Sensor-Adaptive Incremental Learning Framework for Artifact Detection in Satellite Precipitation Data
Paper recorded by Signals 4 on 2026-09-01 in cs.CV. Abstract reproduced from arXiv; link to the original below.
Published 2026-09-01 on arXiv · recorded by Signals 4 on 2026-09-02
Category: cs.CV · 计算机视觉 · first seen 2026-09-02
Abstract
Historically, retrieving rainfall data from satellite imagery has been the domain of space agencies. However, in recent years, the development of cheaper, more compact satellites (SmallSats) capable of detecting rainfall proxies has led to a significant increase in private-sector initiatives for satellite launch and surface precipitation products. This rapid growth has yet to be matched by data va
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Cite this page: A Sensor-Adaptive Incremental Learning Framework for Artifact Detection in Satellite Precipitation Data: the #183 most recent of 237 cs.CV papers we have recorded (as of 2026-09-01). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/a-sensor-adaptive-incremental-learning-framework-for-artifact-detection-in-satel.html
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