| A locally-constrained YOLO framework for detecting small and densely-distributed building footprints Y Xie, J Cai, R Bhojwani, S Shekhar, J Knight International Journal of Geographic Information Science, 2020 | 78 | 2020 |
| Transdisciplinary Foundations of Geospatial Data Science Y Xie, E Eftelioglu, RY Ali, X Tang, Y Li, R Doshi, S Shekhar ISPRS International Journal of Geo-Information 6 (12), 2017 | 49 | 2017 |
| Ring-shaped hotspot detection: A summary of results E Eftelioglu, S Shekhar, D Oliver, X Zhou, MR Evans, Y Xie, JM Kang, ... 2014 IEEE International Conference on Data Mining, 815-820, 2014 | 47 | 2014 |
| A statistically-guided deep network transformation and moderation framework for data with spatial heterogeneity Y Xie, E He, X Jia, H Bao, X Zhou, R Ghosh, P Ravirathinam 2021 IEEE International Conference on Data Mining (ICDM), 767-776, 2022 | 44 | 2022 |
| Statistically-robust clustering techniques for mapping spatial hotspots: A survey Y Xie, S Shekhar, Y Li ACM Computing Surveys (CSUR) 55 (2), 1-38, 2022 | 43 | 2022 |
| Parallel Processing over Spatial-Temporal Datasets from Geo, Bio, Climate and Social Science Communities: A Research Roadmap SK Prasad, D Aghajarian, M McDermott, D Shah, M Mokbel, S Puri, ... IEEE Big Data Congress, 2017 | 43 | 2017 |
| Covid-gan: Estimating human mobility responses to covid-19 pandemic through spatio-temporal conditional generative adversarial networks H Bao, X Zhou, Y Zhang, Y Li, Y Xie Proceedings of the 28th international conference on advances in geographic …, 2020 | 40 | 2020 |
| Significant DBSCAN towards statistically robust clustering Y Xie, S Shekhar Proceedings of the 16th International Symposium on Spatial and Temporal …, 2019 | 39 | 2019 |
| Transforming Smart Cities with Spatial Computing Y Xie, J Gupta, Y Li, S Shekhar Proceedings of the 4th IEEE International Smart Cities Conference (ISC2), 2018 | 38 | 2018 |
| Machine Learning for Data Science Handbook L Rokach, O Maimon, E Shmueli Springer International Publishing, 2023 | 37* | 2023 |
| Crater detection using the morphological characteristics of Chang'E-1 digital elevation models Y Xie, G Tang, S Yan, H Lin IEEE Geoscience and Remote Sensing Letters 10 (4), 885-889, 2013 | 34 | 2013 |
| Ndvi versus cnn features in deep learning for land cover clasification of aerial images A Ramanath, S Muthusrinivasan, Y Xie, S Shekhar, B Ramachandra IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium …, 2019 | 32 | 2019 |
| Fairness by “Where”: A Statistically-Robust and Model-Agnostic Bi-level Learning Framework Y Xie, E He, X Jia, W Chen, S Skakun, H Bao, Z Jian, R Ghosh, ... Proceedings of the AAAI Conference on Artificial Intelligence 36 (11), 12208 …, 2022 | 29 | 2022 |
| Spatial variability aware deep neural networks (svann): A general approach J Gupta, C Molnar, Y Xie, J Knight, S Shekhar ACM Transactions on Intelligent Systems and Technology (TIST) 12 (6), 1-21, 2021 | 28 | 2021 |
| Physics-guided machine learning from simulation data: An application in modeling lake and river systems X Jia, Y Xie, S Li, S Chen, J Zwart, J Sadler, A Appling, S Oliver, J Read 2021 IEEE International Conference on Data Mining (ICDM), 270-279, 2021 | 24 | 2021 |
| A TIMBER Framework for Mining Urban Tree Inventories Using Remote Sensing Datasets Y Xie, H Bao, S Shekhar, J Knight IEEE International Conference on Data Mining (ICDM'18), 2018 | 24 | 2018 |
| Quantifying and reducing registration uncertainty of spatial vector labels on earth imagery W He, Z Jiang, M Kriby, Y Xie, X Jia, D Yan, Y Zhou Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and …, 2022 | 22 | 2022 |
| Physics guided neural networks for time-aware fairness: an application in crop yield prediction E He, Y Xie, L Liu, W Chen, Z Jin, X Jia Proceedings of the AAAI Conference on Artificial Intelligence 37 (12), 14223 …, 2023 | 21 | 2023 |
| Large-scale river mapping using contrastive learning and multi-source satellite imagery Z Wei, K Jia, P Liu, X Jia, Y Xie, Z Jiang Remote Sensing 13 (15), 2893, 2021 | 21 | 2021 |
| Towards spatial variability aware deep neural networks (SVANN): A summary of results J Gupta, Y Xie, S Shekhar arXiv preprint arXiv:2011.08992, 2020 | 21 | 2020 |
Shashi ShekharMcKnight Distinguished University Professor of Computer Science, University of Minnesota在 umn.edu 的电子邮件经过验证
