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Publications |
- R. T. Bhowmik, Y. S. Jung, J. Aguilera, M. Prunicki, K. Nadeau, “A Multi-Modal Wildfire Prediction and Personalized Early-Warning System Based on a Novel Machine Learning Framework,” Journal of Environmental Management, 341, 117908, 2023. (Link)
- R. T. Bhowmik, C. Kandathil, S. P. Most, “Automating the Standardized Cosmesis and Health Nasal Outcomes Survey (SCHNOS) Classification with Convolutional Neural Networks,” Facial Plastic Surgery & Aesthetic Medicine, PMID: 36749153, 2023. (Link)
- R. T. Bhowmik, S. P. Most, “A Personalized Respiratory Disease Exacerbation Prediction Technique Based on a Novel Spatio-Temporal Machine Learning Architecture and Local Environmental Sensor Networks,” Electronics, 11 (16), 2562, 2022. (Link)
- R. Parthasarathy, R. T. Bhowmik, “Quantum Optical Convolutional Neural Network: A Novel Image Recognition Framework for Quantum Computing,” IEEE Access, 9, 103337, 2021. (Link)
- R. T. Bhowmik, “A Multi-Modal Wildfire Prediction and Personalized Early-Warning System Based on a Novel Machine Learning Framework,” arXiv:2208.09079, 2022. (Link)
- R. T. Bhowmik, “A Multi-Modal Respiratory Disease Exacerbation Prediction Technique Based on a Spatio-Temporal Machine Learning Architecture,” arXiv:2103.03086, 2021. (Link)
- R. Parthasarathy, R. T. Bhowmik, “Quantum Optical Convolutional Neural Network: A Novel Image Recognition Framework for Quantum Computing,” arXiv:2012.10812, 2020. (Link)
- R. T. Bhowmik, “A Multi-Modal Wildfire Prediction and Personalized Early-Warning System Based on a Novel Machine Learning Framework,” Stanford BigEarth Hackathon, 2022.