Table 13.
Comparative summary.
| Method | Architecture | Dataset | Accuracy | Interpretability |
|---|---|---|---|---|
| Baig et al. (2022) | CNN ensemble | ALL-IDB | 0.9704 | None |
| Shawly & Alsheikhy (2022) | CNN | ALL-IDB | ≈ 0.97 | None |
| Gupta et al. (2024) | ViT | Custom (10,661) | 0.943 | Attention maps only |
| Zhou et al. (2022) | ViT-CNN hybrid | ALL-IDB | 0.96 | Grad-CAM |
| Almadhor et al. (2023) | DDRNet + attention | ALL-IDB | 0.97 | Grad-CAM |
| Jammal & Dahab (2025) — CausalFormer-HMC | Hybrid + counterfactual | ALL-IDB / C-NMC | 0.98 / 0.95 | Counterfactual XAI |
| Jammal et al. (2025) — Neuro-Bridge-X | Neuro-symbolic ViT | ALL-IDB / C-NMC | 0.98 / 0.95 | Fuzzy + dynamic XAI |
| Meta-Conformer-XAI (this work) | CNN + ViT + DAFF + Meta + RL | ALL-IDB / C-NMC | 0.9924 / 0.9636 | Grad-CAM, SHAP, LIME, IG with quantitative validation |