Dr. S. P. Rajamohana
About
Research Area
Dr. SP. Rajamohana is an Assistant Professor in the Department of Computer Science at Pondicherry University, Karaikal Campus. She obtained her Ph.D. in Spam Review Classification using Bio-Inspired Algorithms from Anna University, Chennai, in 2019. Prior to this, she served for 14 years as an Assistant Professor (Senior Grade) at PSG College of Technology, Coimbatore. Her research area includes Evolutionary Algorithms, Deep Learning, Artificial Intelligence, Quantum Computing, and Remote Sensing. She has published several Scopus indexed journal articles and presented her research work at international conferences, including at Nanyang Technological University (Singapore), Lincoln University (Malaysia), and Gdansk University (Poland). In addition, she serves as a reviewer for prestigious journals such as Soft Computing (Springer), Hindawi, and Elsevier, and holds an NPTEL Elite certificate in Introduction to Quantum Computing: Quantum Algorithms and Qiskit.
Notable & Recent Publications
"Dr.SP Rajamohana et al,,""Hybrid Quantum Graph Neural Network for Brain Tumor MR Image Classification:"" , Journal of Scientific & Industrial Research (JSIR),Volume-84(1),Pages-60-71 (2024).IF-0.7"
Rajamohana, S. P. et al,.. "A Review and Analysis of GAN-Based Super-Resolution Approaches for INSAT 3D/3DR Satellite Imagery using Artificial Intelligence:" Journal of Scientific & Industrial Research (JSIR), Volume 83(6), Pages 627-638, (2024),IF-0.7
Rajamohana, S. P. et al,. ,"Tropical Cyclone Intensity Prediction Using Deep Learning Techniques-A Survey",IEEE Xplore.(2024)(Scopus)
"Rajamohana, S. P. et al,. ""Machine learning techniques for healthcare applications: early autism detection using ensemble approach and breast cancer prediction using SMO and IBK"",Research Anthology on Medical Informatics in Breast and Cervical Cancer, Pages 386-402,IGI Global(2023)(Scopus)"
Rajamohana, S. P. et al,. "Driver drowsiness detection system using hybrid approach of convolutional neural network and bidirectional long short term memory (CNN_BILSTM)",Materials Today: Proceedings,45,2897-2901,(2021),IF -3.1
