Research data and reproducibility records for "Class–Source Confounding and Architecture-Selection Instability under Domain Shift: A Multi-Source Benchmark for Maize Disease and Pest Image Classification"

Study scope and design Image-level prediction labels, source/evaluation manifests, 30 run records, statistical summaries, anonymous rust-assessment labels and retrospective integrity/sensitivity analyses for six maize disease/pest classification configurations with five seeds. Two seeds and optimiza...

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Detalles Bibliográficos

Autores principales:	Hamilton Villamar-Barros, Julián Coronel-Reyes, Vanessa Vergara-Lozano, Alexander Haro-Sarango
Formato:	Conjunto de datos
Lenguaje:	inglés
Publicado:	2026
Materias:	domain shift image classification model reproducibility data provenance image augmentation Smart Agriculture and AI Domain Adaptation and Few-Shot Learning Advanced Neural Network Applications
Acceso en línea:	Enlace permanente (DOI o Handle)
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