Pure data correction enhancing remote sensing image classification with a lightweight ensemble model.

ABSTRACT: The classification of remote sensing images is inherently challenging due to the complexity, diversity, and sparsity of the data across different image samples. Existing advanced methods often require substantial modifications to model architectures to achieve optimal performance, resulting in complex frameworks that are difficult to adapt. To overcome these limitations, we propose a lightweight ensemble method, enhanced by pure data correction, called the Exceptionally Straightforward Ensemble. This approach eliminates the need for extensive structural modifications to models. A key innovation in our method is the introduction of a novel strategy, quantitative augmentation, implemented through a plug-and-play module. This strategy effectively corrects feature distributions across remote s

SUBMITTER: Song H 

PROVIDER: S-EPMC11829047 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature