| Floodnet: A high resolution aerial imagery dataset for post flood scene understanding M Rahnemoonfar, T Chowdhury, A Sarkar, D Varshney, M Yari, ... IEEE Access 9, 89644-89654, 2021 | 210 | 2021 |
| DisCountNet: Discriminating and counting network for real-time counting and localization of sparse objects in high-resolution UAV imagery M Rahnemoonfar, D Dobbs, M Yari, MJ Starek Remote Sensing 11 (9), 1128, 2019 | 38 | 2019 |
| Automatic ice surface and bottom boundaries estimation in radar imagery based on level-set approach M Rahnemoonfar, GC Fox, M Yari, J Paden IEEE Transactions on Geoscience and Remote Sensing 55 (9), 5115, 2017 | 37 | 2017 |
| Deep multi-scale learning for automatic tracking of internal layers of ice in radar data M Rahnemoonfar, M Yari, J Paden, L Koenig, O Ibikunle Journal of Glaciology 67 (261), 39-48, 2021 | 35 | 2021 |
| Smart tracking of internal layers of ice in radar data via multi-scale learning M Yari, M Rahnemoonfar, J Paden, I Oluwanisola, L Koenig, ... 2019 IEEE International Conference on Big Data (Big Data), 5462-5468, 2019 | 23 | 2019 |
| Attractor bifurcation and final patterns of the n-dimensional and generalized Swift-Hohenberg equations M Yari Discrete and Continuous Dynamical Systems: Series B. 7 (2), 441, 2007 | 23 | 2007 |
| Deep ice layer tracking and thickness estimation using fully convolutional networks D Varshney, M Rahnemoonfar, M Yari, J Paden 2020 IEEE International conference on big data (big data), 3943-3952, 2020 | 22 | 2020 |
| Multi-scale and temporal transfer learning for automatic tracking of internal ice layers M Yari, M Rahnemoonfar, J Paden IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020 | 19 | 2020 |
| Deep learning on airborne radar echograms for tracing snow accumulation layers of the Greenland ice sheet D Varshney, M Rahnemoonfar, M Yari, J Paden, O Ibikunle, J Li Remote Sensing 13 (14), 2707, 2021 | 18 | 2021 |
| Radar sensor simulation with generative adversarial network M Rahnemoonfar, M Yari, J Paden IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020 | 18 | 2020 |
| Dynamical transitions of Turing patterns HG Kaper, S Wang, M Yari Nonlinearity 22 (3), 601, 2009 | 14 | 2009 |
| Phase transition analysis of the dynamic instability of microtubules S Yarahmadian, M Yari Nonlinearity 27 (9), 2165, 2014 | 12 | 2014 |
| Snow radar layer tracking using iterative neural network approach O Ibikunle, J Paden, M Rahnemoonfar, D Crandall, M Yari IGARSS 2020-2020 IEEE International Geoscience and Remote Sensing Symposium …, 2020 | 10 | 2020 |
| Airborne snow radar data simulation with deep learning and physics-driven methods M Yari, O Ibikunle, D Varshney, T Chowdhury, A Sarkar, J Paden, J Li, ... IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2021 | 9 | 2021 |
| Automatic polar ice thickness estimation from SAR imagery M Rahnemoonfar, M Yari, GC Fox SPIE Radar Sensor Technology XX 9829, 982902, 2016 | 8 | 2016 |
| Dynamic bifurcation of the periodic Swift-Hohenberg equation JM Han, M Yari Bulletin of the Korean Mathematical Society 49 (5), 923, 2012 | 7 | 2012 |
| Regression Networks for Calculating Englacial Layer Thickness D Varshney, M Rahnemoonfar, M Yari, J Paden 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS, 2393 …, 2021 | 6 | 2021 |
| Refining Ice Layer Tracking through Wavelet combined Neural Networks D Varshney, M Yari ICML 2021 Workshop on Tackling Climate Change with Machine Learning, 2021, 2021 | 5 | 2021 |
| Deep ice layer tracking and thickness estimation using fully convolutional networks M Rahnemoonfar, D Varshney, M Yari, J Paden | 5 | 2020 |
| The first automatic method for mapping the pothole in seagrass M Rahnemoonfar, M Yari, A Rahman, R Kline Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 5 | 2017 |
