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Sivangi Ravikanth

CVR College Of Engineering

Hyderabad

India

SCHOLARLY PAPERS

3

DOWNLOADS

162

TOTAL CITATIONS

1

Scholarly Papers (3)

1.

A Scalable and Robust Framework for Advanced Semi Supervised Learning Supporting Universal Applications

Proceedings of the 3rd International Conference on Optimization Techniques in the Field of Engineering (ICOFE-2024)
Number of pages: 17 Posted: 06 Jan 2025
Sr Data Engineer, Exelon, RGM College of Engineering and Technology, CIGNA, Terna Engineering College, Research Assistant and CVR College Of Engineering
Downloads 76 (837,727)

Abstract:

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semi-supervised learning, scalable frameworks, robust machine learning, domain adaptability, hybrid loss functions, explainable AI, SHAP, noisy data handling, text classification, image classification, graph neural networks, domain shifts, dynamic feature transformation, data augmentation, pseudo-la

2.

Enhancing Machine Learning-Enhanced Flexible Hydrophone Sensors

Proceedings of the 3rd International Conference on Optimization Techniques in the Field of Engineering (ICOFE-2024)
Number of pages: 12 Posted: 21 Dec 2024
Symbiosis International (Deemed University), Hyderabad Institute of Technology and Management, K S R COLLEGE OF ENGINEERING, R.M.K College of Engineering and Technology and CVR College Of Engineering
Downloads 63 (961,006)
Citation 1

Abstract:

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Speech analysis, Flexible hydrophone sensors, Acoustic technology, Machine learning advancements, Innovative developments.

3.

A Scalable and Robust Framework for Advanced Semi Supervised Learning Supporting Universal Applications

Number of pages: 17 Posted: 08 May 2025
CIGNA, RGM College of Engineering and Technology, Terna Engineering College, Research Assistant and CVR College Of Engineering
Downloads 23 (1,411,822)

Abstract:

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semi-supervised learning, scalable frameworks, robust machine learning, domain adaptability, hybrid loss functions, explainable AI, SHAP, noisy data handling, text classification, image classification, graph neural networks, domain shifts, dynamic feature transformation, data augmentation, pseudo-labelling, real-world applications, interpretability, universal learning frameworks, large-scale datasets, SSL challenges