0000-0003-3981-5971 About
Dr. Payel Sengupta holds both M.Tech and Ph.D. degrees in Computer Science and Engineering, and has established a strong academic and research profile in the domain of AI, Machine learning, Deep learning, Image Processing. Her areas of expertise include programming methodologies, machine learning, data-driven technologies, and emerging trends in computer science. She is currently serving as an Assistant Professor in the Department of Computer Science and Engineering at Brainware University
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Publications (19)
- Impact of Class Imbalance, SMOTE, and Threshold Optimization on Prostate Cancer Prediction Models Save
- DATA-DRIVEN THERMAL SIGNAL MODELING FOR MATERIAL AND HEAT MANAGEMENT OPTIMIZATION IN ELECTRIC VEHICLE BATTERIES Save
- Improving Diabetic Retinopathy Prediction with Stacked Generalization and Out-of-Fold Learning Save
- A comprehensive machine learning approach for early detection of cardiovascular diseases using machine learning techniques Save
- Closing Price Prediction of the Stocks Using Gradient Descent Based Linear Regression Method Save
- Recent Trends in Data-Efficient Scene Text Recognition: A Survey on Zero-Shot and Few-Shot Learning Save
- Enhanced Lung and Oesophageal Cancer Detection Using Aggregated Joint Assembly for Decision-making (AJAD): A Novel Classifier Save
- Stacking Classifier for Enhanced Detection of Thyroid Cancer Recurrence- A Novel Approach Save
- A Theoritical Study On Computational Linguistics And Conversational Agents:From Scripted Interactions To Contextualized Cognition Save
- Optimising Educational Performance through Clustering Algorithm Evaluation Save