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Author

G. Thirupati

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Aug 2026

Vision-Threatening Diabetic Retinopathy Detection Using EfficientNetB4: A Two-Stage Transfer Learning Approach

ABSTRACT Threatening Diabetic Retinopathy (VTDR) remains an advanced stage of ophthalmic complications secondary to diabetes and is characterized as a major, preventable cause of irreversible vision loss. In this paper, we propose an automated deep learning framework to classify retinal fundus images into Non-VTDR (He...

Vannala Harish, G. Thirupati · 0 citations
Open access Aug 2026

EEG-Based Emotion Recognition Using CWT Scalograms and MobileNetV2 Transfer Learning

A deep learning framework that integrates CWT-based RGB scalogram generation and transfer learning with MobileNetV2 for reliable emotion classification using EEG, and proves that the EEG-to-scalogram conversion, in conjunction with LDTL, is a promising, efficient solution for real-time generalized emotion recognition a...

K. Archana, G. Thirupati · 0 citations
Aug 2026

Attention-Based Deep Learning Framework for Multi-Class Classification of Liver Cirrhosis Stages Using Clinical and Biochemical Biomarkers

The attention model proposed is a strong, interpretable, and clinically applicable model for classifying liver cirrhosis stages and may be applied to computer-aided diagnosis systems and clinician-targeted risk stratification of patients.

P. Kavya, G. Thirupati · 0 citations
Open access Aug 2026

Breast Cancer Classification in Ultrasound Images Using Two-Phase EfficientNetB7 Transfer Learning

A systematic but innovative two phases transfer learning’sbased deep learning classification framework is developed using popular EfficientNetB7 architecture architecture for breast cancer classification which encompasses formalisation into components like data augmentation, progressive fine-tuning and adaptive learnin...

M. Kavya, G. Thirupati · 0 citations
Aug 2026

DenseNet169-Enabled High-Accuracy Automated Detection System for Cotton Leaf Diseases Using Deep Transfer Learning

The new high-water mark physiological plant disease diagnosis that is established here is an important step toward ultimately real-world applicability as“adaptive components of precision agriculture to monitor crop health and protect yield.

Rebally.Vijay Kumar, G. Thirupati · 0 citations

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