Dr C Heltin Genitha
Professor
| Department of Information Technology
St. Josephs College of Engineering
Tamil Nadu
Expertise:
Computer Science Artificial Intelligence
48
Publications
1
Projects
195
Scopus Citations
158
CrossRef
21 Years 3 Months Total Experience
Scopus
195
Citations
9
h-index
CrossRef
158
Citations
8
h-index
Google Scholar
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Personal Details
Doctor of Philosophy
2014
Sultan Qaboos University, Muscat
Master of Engineering
2005
BABU BANARASI DAS INSTITUTE OF TECHNOLOGY AND MANAGEMENT, LUCKNOW
Bachelor of Engineering
2003
N/A
Professor
Jul 2022 – Present
St. Josephs College of Engineering
| Department of Information Technology
Associate Professor
Jun 2012 – Jun 2022
St. Josephs College of Engineering
| Department of Information Technology
Assistant Professor
Feb 2010 – May 2012
St. Josephs College of Engineering
| Department of Information Technology
Lecturer
Jun 2005 – Jan 2010
St. Josephs College of Engineering
| Department of Information Technology
Engineering and Technology
Scholarly Work
Super-Resolution Mapping Algorithms for Accurate Estimation of the Capacity of Reservoirs of Chennai City using Satellite Images
CompletedAutomated Framework for Detection and Classification of Breast Abnormality using Breast Thermograms
Smart Machine Learning Based Approach Integrated With Internet Of Things (IOT) To Predict The Plant Growth And Disease
Dr.C. Heltin Genitha
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Application No. :
202241065125
Filed :
14-11-2022
Published :
25-11-2022
Published
Scholarly Publications
Deep Learning based Approach to Assess the Impact of Cyclone Ockhi on Coconut Tree Population using Satellite Images
Scopus: 1
A Data-Driven Approach to Customer Churn Prediction in Banking: A Comparative Study of Machine Learning Techniques
Stage-Aware Hybrid Rule-Guided Attention Framework for Explainable Chronic Kidney Disease Prediction
A Multi-Feature Adaptive Approach with Deep Action Ensemble Model for Human Action Recognition
Spatio-Temporal Forecasting of Urban Microclimate Dynamics Using Deep Learning on Satellite Imagery
Predictive Modeling for Credit Card Fraud Detection System Using Random Forest Ensemble Approach
10.1109/IC3ET64989.2026.11467559
Scopus: 1
Deep Learning-Based Intelligent System for Waste Detection and Segregation in Aquatic Environments
Multi-Modal Hybrid Attention-based LSTM-CNN Framework for Real-Time Gold Price Forecasting
Showing 1 to 8 of 48 publications