Author

Srinivas Koppu

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Open access Aug 2026

Multi-paradigm Vision Transformer ensemble with regional attention and MLP meta-fusion for explainable dermoscopic skin lesion classification

An exhaustive explainability framework comprising Regional Attention Maps, GradCAM++, SHAP, and t-SNE provides complementary spatial, gradient-based, pixel-level, and embedding-level interpretability, ensuring clinical trust, transparency, and trustworthiness expected from an automated dermoscopy system.

NE. Sravani, Srinivas Koppu · Frontiers in Medicine · 0 citations

#federated learning Open access Sep 2026

A robust privacy-preserving federated framework for kidney CT image classification using transfer learning models

A novel federated transfer learning framework for accurate classification of renal abnormalities using 12,446 kidney CT scan images and simultaneously preserves data privacy is proposed, highlighting its potential for deployment in distributed clinical environments for kidney disease diagnosis.

Sai Sri Hemantha Konala, Srinivas Koppu · Frontiers in Artificial Inte... · 0 citations

#explainable ai Open access Sep 2026

Explainable ensemble transfer learning for skin lesion classification with multi-method explainability validation

Quantitative evaluation using TMAI and complementary XAI methods provides additional evidence that the model's predictions are grounded in clinically relevant lesion regions rather than background artefacts, supporting the potential of the framework for accurate and interpretable automated skin lesion classification.

NE. Sravani, Srinivas Koppu · Frontiers in Public Health · 0 citations

Open access Aug 2026

Explainable and reliable kidney CT image classification using self-supervised DeiT-Tiny transformer

A novel two-stage deep learning architecture that integrates self-supervised representation learning with supervised classification for kidney CT image analysis using a publicly available kidney CT image dataset is introduced.

Sai Sri Hemantha Konala, Srinivas Koppu · Frontiers in Medicine · 0 citations