MODAMS: design of a multimodal object-detection based augmentation model for satellite image sets

MODAMS: design of a multimodal object-detection based augmentation model for satellite image sets

Abstract Efficient image augmentation for hyperspectral satellite images requires design of multiband processing models that can assist in improving classification performance for different application scenarios. Existing models either work on dynamic band fusions, or use deep learning techniques fo...

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Bibliographic Details
Main Authors: Rahul Malik, Rachit Garg, Korhan Cengiz, Nikola Ivković, Adnan Akhunzada
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Augmentation
Satellite
Object
Detection
YOLO
Importance
Online Access:https://doi.org/10.1038/s41598-025-93766-z
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