Building consistency in explanations: Harmonizing CNN attributions for satellite-based land cover classification

Building consistency in explanations: Harmonizing CNN attributions for satellite-based land cover classification

Explainable machine learning has gained substantial attention for its role in enhancing transparency and trust in computer vision applications. Attribution methods like Grad-CAM and occlusion sensitivity analysis are frequently used to identify how features contribute to predictions of neural networ...

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Bibliographic Details
Main Authors: Timo T. Stomberg, Lennart A. Reißner, Martin G. Schultz, Ribana Roscher
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Machine Learning with Applications
Subjects:
Explainable machine learning
Attribution methods
Feature representations
Feature space
Land cover
Satellite imagery
Online Access:http://www.sciencedirect.com/science/article/pii/S2666827025000362
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