SMOG: an adaptive hybrid oversampling framework using SMOTE and conditional GAN for difficulty-aware learning on imbalanced data

Jatinder Kaur Vimal Parmar B. K. Rao Arikatla Jaya Lakshmi V. Vivek Sarbeswara Hota B. Ankayarkanni Devendra Singh Apurav Gautam

Aug 2026 · Evolutionary Intelligence · Vol 19 · 0 citations · 33 references

TL;DR

SMOG, an adaptive hybrid oversampling framework that integrates the Synthetic Minority Over-sampling Technique with a Conditional Generative Adversarial Network (GAN)-based difficulty-aware learning strategy, highlights the effectiveness of adaptive hybrid generative strategies for intelligent learning on imbalanced data.

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