THRUST AREAS OF RESEARCH

The Computer Science Department at L.R.G. Government Arts College for Women is dedicated to advancing technical knowledge through focused research in several key areas.

Our thrust areas of research include

• Data Mining
• Image Processing
• Networks
• Artificial Intelligence and Machine Learning
• Robotics
• Vision and Graphics

These areas represent the major research activities in the Department of Computer Science. Faculty and Research Scholars has developed new ideas to achieve results in all aspects.

APPROVED RESEARCH GUIDES

RECENT RESEARCH PUBLICATIONS

The Computer Science Department at L.R.G. Government Arts College for Women has made significant contributions to various fields of Computer Science through its research publications. The departments research covers a wide range of topics, including Data Mining, Networks, Artificial Intelligence and Image Processing.

• ANBARASI, “DEEP ADAPTIVE INTUITIONSTIC EXPERT SYSTEM FOR EARLY PREDICTION OF AUTISM SPECTRUM DISORDER AMONG CHILDREN” in Journal of Nonlinear Analysis and Optimization, ISSN 1906 – 9685, Volume 15, Issue 01, Page 358, 2024.
• ANBARASI, “Determining Adverse Effects of COVID – 19 Vaccination using Machine Learning and Deep Learning Classification and Identification” in Journal of Springer Journal Acceptance Received 2024.
• SUNDARAVALLI “Automated Feature Extraction and Classification of COVID – 19 Chest X-ray Images using Convolutional Neural Networks and XGBoost Algorithms” in Journal of Basic Science and Engineering, Volume21 No.1(2024), ISSN : 1005 – 0930, Page 1338-1362, 2024.
• SUHASINI and N. Vimala “Prediction of Fake Twitters using AdaBoost – Based Neuro Evolution of Augmenting Topologies Algorithm”, in Journal of Advances in Computing and Information (SPRINGER), Volume 1, ISSN 1876-1119, Page no : 15 – 26, 2023.
• KOMALAVALLI and R. VIDYABANU “COVID – 19 Vaccine Hesitancy Tweets Detection using Majority Voting Based Ensemble Classification “ in Shodhsanhita : Journal of Fundamental & Comparative Research (UGC CARE List), pp.193-202, Volume IX, Issue II, 2023.
• KOMALAVALLI and R. VIDYABANU “Sentiment Analysis and Hybrid Two-Tier Meta – Learning Classification for COVID 19 Rumor Tweet Discovery” in Journal of METSZET Journal (SCOPUS), Volume 8, Issue 11, pp. 333-351, 2023.
• SUGANTHI “COVID – 19 Diagnosis using Chaotic Logistic Map Based Modified Whale Optimization : A Robust Feature and Parameter Selection Approach” in Journal of Revue d’ Intelligence Artificielle, Volume 37, Issue 5, 2023.

• To view full list of publications, CLICK HERE.