Official implementation of the published paper "Tri-Net: Unified Deep Learning for Skin Lesion and Symptom-Based Monkeypox Detection" (Scopus Q1, SCI-E, IF 3.9), featuring a reproducible Tri-Net v2 framework with modern backbones, feature fusion, explainability, and benchmarking.
My dissertation research project proposing novel Hybrid CNN–Transformer A/B models and scalable guidance modules for investigating shortcut-learning mitigation in brain tumour MRI classification when pixel-level masks are unavailable.
