Research output per year
Research output per year
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
Fingerprint
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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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
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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.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 -
Automatic Detection of Tuberculosis bacilli from Conventional Sputum Smear Microscopic Images Using Densely Connected Convolutional Networks
Panicker, R. O. & Sabu, M. K., 07-2022, In: SN Computer Science. 3, 4, 263.Research output: Contribution to journal › Article › peer-review
9 Citations (Scopus)