| U-net and its variants for medical image segmentation: A review of theory and applications N Siddique, S Paheding, CP Elkin, V Devabhaktuni IEEE access 9, 82031-82057, 2021 | 1416 | 2021 |
| Advances on localization techniques for wireless sensor networks: A survey TJS Chowdhury, C Elkin, V Devabhaktuni, DB Rawat, J Oluoch Computer Networks 110, 284-305, 2016 | 199 | 2016 |
| Trends in deep learning for medical hyperspectral image analysis U Khan, S Paheding, CP Elkin, VK Devabhaktuni IEEE Access 9, 79534-79548, 2021 | 66 | 2021 |
| Localization in wireless sensor networks: A Dempster-Shafer evidence theoretical approach C Elkin, R Kumarasiri, DB Rawat, V Devabhaktuni Ad Hoc Networks 54, 30-41, 2017 | 35 | 2017 |
| A preliminary work on visualization-based education tool for high school machine learning education AA Reyes, C Elkin, Q Niyaz, X Yang, S Paheding, VK Devabhaktuni 2020 IEEE integrated STEM education conference (ISEC), 1-5, 2020 | 26 | 2020 |
| its variants for medical image segmentation: A review of theory and applications., 2021, 9 N Siddique, S Paheding, CP Elkin, VD U-net DOI: https://doi. org/10.1109/ACCESS, 82031-82057, 2021 | 17 | 2021 |
| Pilot skill level and workload prediction for sliding-scale autonomy SKR Nittala, CP Elkin, JM Kiker, R Meyer, J Curro, AK Reiter, KS Xu, ... 2018 17th IEEE International Conference on Machine Learning and Applications …, 2018 | 16 | 2018 |
| Novel human-in-the-loop (HIL) simulation method to study synthetic agents and standardize human–machine teams (HMT) P Damacharla, P Dhakal, JP Bandreddi, AY Javaid, JJ Gallimore, C Elkin, ... Applied Sciences 10 (23), 8390, 2020 | 10 | 2020 |
| Comparative analysis of machine learning techniques in assessing cognitive workload C Elkin, V Devabhaktuni Advances in Neuroergonomics and Cognitive Engineering: Proceedings of the …, 2020 | 7 | 2020 |
| U-Net and its variants for medical image segmentation: Theory and applications. arXiv 2020 N Siddique, P Sidike, C Elkin, V Devabhaktuni arXiv preprint arXiv:2011.01118, 0 | 6 | |
| Fundamental cognitive workload assessment: A machine learning comparative approach C Elkin, S Nittala, V Devabhaktuni Advances in Neuroergonomics and Cognitive Engineering: Proceedings of the …, 2018 | 5 | 2018 |
| Analysis of alternatives for neural network training techniques in assessing cognitive workload C Elkin, V Devabhaktuni Advances in Neuroergonomics and Cognitive Engineering: Proceedings of the …, 2019 | 2 | 2019 |
| Educational prototype demonstrating frequency spectrum sharing through channel borrowing and priority assignment B Keneni, B Austin, C Elkin, V Devabhaktuni 2017 IEEE International Conference on Electro Information Technology (EIT …, 2017 | 1 | 2017 |
| Improved Prediction of Steel Hardness Through Neural Network Regression C Elkin, R Bathla, T Poplawski, S Agashe, V Devabhaktuni AISTech 2021, 40-45, 2021 | | 2021 |
| Development of Adaptive Computational Algorithms for Manned and Unmanned Flight Safety CP Elkin The University of Toledo, 2018 | | 2018 |
| Verification of physiological data collection C Elkin, V Devabhaktuni Proc. 2016 Safe and Secure Systems & Software Symposium (S5), Dayton, OH …, 2016 | | 2016 |
| Development of novel computational algorithms for localization in wireless sensor networks through incorporation of Dempster-Shafer evidence theory CP Elkin University of Toledo, 2015 | | 2015 |
| COVID-19 Spread Prediction: A Comparative Study P Damacharla, RR Junuthula, C Elkin, S Kumar Engineering Archive, 0 | | |
