Gokul Gopakumar

Amrita Vishwa Vidyapeetham

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G. Angeline Prasanna

Amrita Vishwa Vidyapeetham

Raj Cibin

Amrita Vishwa Vidyapeetham

Chellu Vyshnavi

Amrita Vishwa Vidyapeetham

Dwarapu Subham

Amrita Vishwa Vidyapeetham

Suja Palaniswamy

Amrita Vishwa Vidyapeetham

S Gokulan

Amrita Vishwa Vidyapeetham

K. Murali

Indian Institute of Technology Madras

M. Rajesh

Amrita Vishwa Vidyapeetham

Jewel Shine

Amrita Thakur

Amrita Vishwa Vidyapeetham

Cooperative Institutions

Amrita Vishwa Vidyapeetham

Karpagam Academy of Higher Education

Bharathiar University

Indian Institute of Technology Madras

University of Agricultural Sciences, Bangalore

Chhattisgarh Kamdhenu Vishwavidyalaya

International Institute of Information Technology

Sri Ramakrishna Institute of Paramedical Sciences

University of Reggio Calabria

National Institute of Technology Tiruchirappalli

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Enhancing Code Insights through Semantic Change Impact Evaluation

2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT) (2024)

Chellu Vyshnavi Raj Cibin Gokul Gopakumar G. Angeline Prasanna Meena Belwal

Code (set theory)

10.1109/icccnt61001.2024.10725350

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Improved Security of Network Clock Synchronization in Wireless Sensor Networks

B Venkat Vinod Kumar Gokul Gopakumar Dwarapu Subham K. Murali

10.1109/amathe61652.2024.10582222

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Citations (1)

Applying Machine Learning Algorithms to Investigate Cervical Cancer

Apurvanand Sahay Gokul Gopakumar S Gokulan Dwarapu Subham Amrita Thakur

Cervical cancer is a significant health challenge globally, particularly in regions with limited access to healthcare resources. Timely and accurate classification of cervical cancer risk is crucial for effective interventions and personalized treatment plans. The paper provides an overview of preliminary results in cervical cancer risk classification, with a focus on three machine learning algorithms namely Support Vector Machines, Capsule CNN and CNN. Support Vector Machine (SVM), Capsule Network, and Convolution Neural Network have emerged as promising methods to predict cervical cancer risk based on various risk factors and biomarkers. These algorithms analyze the available datasets on Cervical Cancer from Kaggle and identify complex patterns, demonstrating potential risk in improving cancer detection accuracy. In addition, we emphasize the importance of prevention measures, including HPV vaccination and regular screenings, to combat cervical cancer effectively. By combining innovative classification algorithms with preventive efforts, we can enhance cervical cancer management and improve patient outcomes worldwide.

10.1109/iitcee59897.2024.10467311

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Citations (1)

A Novel approach for detecting Fibroids in Uterus using Deep Learning models

2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT) (2024)

Chellu Vyshnavi Raj Cibin Gokul Gopakumar G. Angeline Prasanna B. Sreevidya

10.1109/icccnt61001.2024.10724029

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A Novel Approach for Phishing Website Detection using Deep Learning Models

Chellu Vyshnavi Raj Cibin Gokul Gopakumar G. Angeline Prasanna Suja Palaniswamy

Phishing