Personal profile
Research interests
machine learning, deep learning, image processing, medical imaging, teechnology adoption
Experience
16 years of taching experience
Awards and recognition:
UGC NET 2012 qualified
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Dive into the research topics where Rani Oomman Panicker is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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An Explainable Multi-Level Framework for Cervical Cancer Detection Using Traditional Computer Vision and Deep Learning
Chawla, M., Chakraborty, P., Sunderrajan, S. & Panicker, R. O., 2026, In: IEEE Access. 14, p. 12273-12296 24 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Impact of COVID-19 Among College Students Academic, Financial, and Physical Matters: A Quantitative Study
Panicker, R. O., Isaac, J. & Navas, S. S., 2026, Information System Design: Big Data Analytics and Data Science - Proceedings of 9th International Conference on Information System Design and Intelligent Applications ISDIA 2025. Bhateja, V., El Barachi, M., Azar, A. T. & Sharma, D. K. (eds.). Springer Science and Business Media Deutschland GmbH, p. 391-401 11 p. (Lecture Notes in Networks and Systems; vol. 1539 LNNS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Automatic detection of Parkinson's disease using machine learning and deep learning: A recent literature review
Panicker, R. O., Yashasvi, D., James, J. & Ittappa, S., 01-2025, In: Ethics, Medicine and Public Health. 33, 101079.Research output: Contribution to journal › Review article › peer-review
1 Link opens in a new tab Citation (Scopus) -
Drone Flight Dataset and Lightweight LSTM-Based Wind Estimation for Semi-Autonomous Quadcopter Control
Shankar, R. S., Siotia, V. & Panicker, R. O., 2025, (Accepted/In press) In: IEEE Access. 13, p. 203057-203076 20 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Hybrid Vector Auto Regression and Tree-Based Ensembles for Energy Load Forecasting: A Case Study
Guha, S., Katyayanan, S., Mallya, G. & Panicker, R. O., 2025, In: IEEE Access. 13, p. 151773-151787 15 p.Research output: Contribution to journal › Article › peer-review
Open Access