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G. Thirupati

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Open access Aug 2026

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

EEG-based emotion recognition is an important task in affective computing; however, conventional machine learning methods are limited in reliably extracting emotional features because brain signals are highly non-stationary and noisy. To overcome the limitation, we present a deep learning framework that integrates CWT-...

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

ABSTRACT liver cirrhosis staging is crucial to enhance prognosis among patients and optimize the therapeutic approach. An attention-based deep learning framework for automated cirrhosis stage classification using routinely collected clinical and biochemical features As solution 1: A dataset of 25,000 patient records w...

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

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

Breast cancer is a leading cause of cancer morbidity and mortality among women globally, emphasizing the need for accurate and timely diagnostic methods. A systematic but innovative two phases transfer learning based deep learning classification framework is developed using popular EfficientNetB7 architecture architect...

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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