Data Leakage in Patch-Based Hyperspectral Image Classification: Quantifying the Impact of Spatial Overlap
Paper recorded by Signals 4 on 2026-10-06 in cs.CV. Abstract reproduced from arXiv; link to the original below.
Published 2026-10-06 on arXiv · recorded by Signals 4 on 2026-10-07
Category: cs.CV · 计算机视觉 · first seen 2026-10-07
Abstract
Patch-based learning improves hyperspectral image (HSI) classification by exploiting local spectral-spatial information, but random train-test sampling from the same image can cause spatial patch overlap, leading to data leakage and optimistic performance estimates. This paper investigates same-class train-test spatial overlap in patch-based HSI classification using two measures: overlap percentag
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Cite this page: Data Leakage in Patch-Based Hyperspectral Image Classification: Quantifying the Impact of Spatial Overlap: the #340 most recent of 756 cs.CV papers we have recorded (as of 2026-10-06). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/data-leakage-in-patch-based-hyperspectral-image-classification-quantifying-the-i.html
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