Energy and Performance Benchmarking of Deep Learning Models for Breast Cancer Detection

arXiv:2608.09996 · eess.IV, cs.AI, cs.CV, cs.LG · Submitted 2026-08-07 · Read on arXiv

Samar Garrab, Ghada Achour

eess.IV, cs.AI, cs.CV, cs.LG

Submitted: 2026-08-07

Updated: 2026-08-12

Comments: Accepted at ICMLA 2026 (IEEE International Conference on Machine Learning and Applications). Camera-ready version submitted

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 55× in this paper · explained in 1 episode
• Transformer — 25× in this paper · explained in 2 episodes
• Transformers — 15× in this paper · explained in 2 episodes
• Deep Learning — 9× in this paper
• Augmentation — 7× in this paper · explained in 2 episodes
• AUC — 6× in this paper · explained in 2 episodes
• Data Augmentation — 4× in this paper · explained in 10 episodes
• Hybrid Architecture — 4× in this paper · explained in 2 episodes
• Hybrid Model — 4× in this paper · explained in 2 episodes
• Benchmarking — 3× in this paper · explained in 4 episodes
• Computational Efficiency — 3× in this paper · explained in 2 episodes
• Hybrid Architectures — 3× in this paper · explained in 3 episodes
• Hybrid Models — 3× in this paper · explained in 2 episodes
• Artificial Intelligence — 2× in this paper
• Convolutional Neural Networks (CNNs) — 2× in this paper · explained in 3 episodes
• Generalization — 2× in this paper · explained in 14 episodes
• Overfitting — 2× in this paper · explained in 2 episodes
• Robustness — 2× in this paper · explained in 6 episodes
• Area Under the ROC Curve — 1× in this paper
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Class Imbalance — 1× in this paper · explained in 3 episodes
• Data Leakage — 1× in this paper · explained in 2 episodes
• Energy Efficiency — 1× in this paper · explained in 4 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Information Leakage — 1× in this paper · explained in 2 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Transfer Learning — 1× in this paper · explained in 16 episodes
• Transformer Model — 1× in this paper · explained in 2 episodes
• Transformer Models — 1× in this paper · explained in 3 episodes

Sources

• EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks
• Quantifying the Carbon Emissions of Machine Learning

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