Dr. Kavipriya K
Assistant Professor, Department of CS and Applications
Profile
Dr. Kavipriya K
Assistant Professor, Department of Computer Science and Applications
Dr. Kavipriya K is a distinguished educator with over a decade of teaching experience, widely recognized for her expertise in academic research and her commitment to mentoring students toward scholarly excellence and professional growth. She holds a Master’s degree in Computer Applications from Anna University, Chennai, and an M.Phil. in Computer Science from Alagappa University, Karaikudi. She earned her Ph.D. in Computer Science from CHRIST (Deemed to be University), Bangalore, with a specialization in Medical Image Processing.
Her research interests span across Medical Image Processing, Computer Vision, Pattern Recognition, and Machine Learning, where she continues to contribute through scholarly work and academic engagement.
Area
Qualification
MCA., MPhil., Ph.D
Experience
10 years
Publications
Kavipriya, K., and Manjunatha Hiremath. Analysis of Benchmark Image Pre-Processing Techniques for Coronary Angiogram Images. 2021 International Conference on Innovative Trends in Information Technology (ICITIIT). IEEE, 2021.
Kavipriya, K., and Manjunatha Hiremath. Computational Method to Extract the Keyframe from Angiogram Video. Journal of Algebraic Statistics 13.3 (2022): 3088-3097.
Kavipriya, K., and Manjunatha Hiremath. A Novel Approach for Segmenting Coronary Artery from Angiogram Videos. IoT Based Control Networks and Intelligent Systems: Proceedings of 3rd ICICNIS 2022. Singapore: Springer Nature, 2022. 191-200.
Kavipriya, K., and Manjunatha Hiremath. Advanced Computational Method to Extract Heart Artery Region. International Journal of Engineering Trends and Technology, vol. 70, no. 6, 2022. doi: 10.14445/22315381/IJETT-V70I6P237.
Kavipriya, K., and Manjunatha Hiremath. Identification of Coronary Artery Stenosis Based on Hybrid Segmentation and Feature Fusion. Automatika 64.3 (2023): 622-633.
Patil, Ashwini P., Manjunatha Hiremath, and Kavipriya, K. A Study of Preprocessing Techniques on Digital Microscopic Blood Smear Images to Detect Leukemia. Data Science and Security: Proceedings of IDSCS 2022. Singapore: Springer Nature, 2022. 275-282.
Thomas, Libin, et al. On Combinatorial Handoff Strategies for Spectrum Mobility in Ad Hoc Networks: A Comparative Review. ICT with Intelligent Applications: Proceedings of ICTIS 2021, Volume 1 (2021): 727-741.
FDP
Recent Advancements in Machine Learning and Artificial Intelligence – CHRIST (Deemed to be University)
Paper Presentations
Analysis of Benchmark Image Pre-Processing Techniques for Coronary Angiogram Images – Presented at the International Conference on Innovative Trends in Information Technology (ICITIIT-2021), IEEE.
A Novel Approach for Segmenting Coronary Artery from Angiogram Videos – Presented at the International Conference on IoT Based Control Networks and Intelligent Systems (ICICNIS-2022), Springer.
Advanced Computational Method to Extract Heart Artery Region – Presented at the International Journal of Engineering Trends and Technology (IJETT) Conference, 2022.
A Study of Preprocessing Techniques on Digital Microscopic Blood Smear Images to Detect Leukemia – Presented at the International Conference on Data Science Computation and Security (IDSCS-2022), Springer.
Resource Person
- Resource Person for the workshop ‘the implementation of Total Physical response method in learning classroom’ at Evangeline Matriculation Higher Secondary School- Coimbatore.
- Resource Person for a Ten-Day workshop on Communicative English for Beginners, at Snehagiri Society, Kerala.
- Resource Person for Soft skill training at the Department of Computer Science and Applications, Christ Academy Institute For Advanced Studies.
- Resource Person for ‘An Advanced Communicative English workshop’, at Snehagiri Society, Kerala.
- Resource Person for a Guest Session, at Hindustan University.
- Resource Person for a Guest Session, at Vignan University .
- Resource Person for a Guest Session, at Jain University.
Patents
A Computer Vision Based System for Stenosis Detection and Recognition in Coronary Angiogram Image and A Method Thereof
