| Tropical cyclone intensity estimation using a deep convolutional neural network R Pradhan, RS Aygun, M Maskey, R Ramachandran, DJ Cecil IEEE Transactions on Image Processing 27 (2), 692-702, 2017 | 248 | 2017 |
| Three years of the lightning imaging sensor onboard the international space station: Expanded global coverage and enhanced applications RJ Blakeslee, TJ Lang, WJ Koshak, D Buechler, P Gatlin, DM Mach, ... Journal of Geophysical Research: Atmospheres 125 (16), e2020JD032918, 2020 | 120 | 2020 |
| Deepti: Deep-learning-based tropical cyclone intensity estimation system M Maskey, R Ramachandran, M Ramasubramanian, I Gurung, B Freitag, ... IEEE journal of selected topics in applied Earth observations and remote …, 2020 | 67 | 2020 |
| Foundation models for generalist geospatial artificial intelligence J Jakubik, S Roy, CE Phillips, P Fraccaro, D Godwin, B Zadrozny, ... CoRR, 2023 | 58 | 2023 |
| Using sensor web protocols for environmental data acquisition and management H Conover, G Berthiau, M Botts, HM Goodman, X Li, Y Lu, M Maskey, ... Ecological Informatics 5 (1), 32-41, 2010 | 43 | 2010 |
| Advancing AI for Earth science: A data systems perspective M Maskey ESA EO Phiweek, 2020 | 34 | 2020 |
| Croissant: A Metadata Format for ML-Ready Datasets M Akhtar, O Benjelloun, C Conforti, P Gijsbers, J Giner-Miguelez, N Jain, ... Proceedings of the Eighth Workshop on Data Management for End-to-End Machine …, 2024 | 28 | 2024 |
| Detection of transverse cirrus bands in satellite imagery using deep learning J Miller, U Nair, R Ramachandran, M Maskey Computers & Geosciences 118, 79-85, 2018 | 26 | 2018 |
| NASA framework for the ethical use of artificial intelligence (AI) E McLarney, Y Gawdiak, N Oza, C Mattmann, M Garcia, M Maskey, ... | 20 | 2021 |
| Applying deep learning to hail detection: A case study M Pullman, I Gurung, M Maskey, R Ramachandran, SA Christopher IEEE Transactions on Geoscience and Remote Sensing 57 (12), 10218-10225, 2019 | 18 | 2019 |
| Cloud Hosted Real‐time Data Services for the Geosciences (CHORDS) B Kerkez, M Daniels, S Graves, V Chandrasekar, K Keiser, C Martin, ... Springer Berlin Heidelberg, 2016 | 17 | 2016 |
| High-Performance and Disruptive Computing in Remote Sensing: HDCRS—A new Working Group of the GRSS Earth Science Informatics Technical Committee [Technical Committees] G Cavallaro, DB Heras, Z Wu, M Maskey, S Lopez, P Gawron, M Coca, ... IEEE geoscience and remote sensing magazine 10 (2), 329-345, 2022 | 15 | 2022 |
| DMLR: Data-centric Machine Learning Research--Past, Present and Future L Oala, M Maskey, L Bat-Leah, A Parrish, NM Gürel, TS Kuo, Y Liu, R Dror, ... arXiv preprint arXiv:2311.13028, 2023 | 12 | 2023 |
| Exploring the use of PlanetScope data for particulate matter air quality research J Le Roux, S Christopher, M Maskey Remote Sensing 13 (15), 2981, 2021 | 12 | 2021 |
| Machine learning lifecycle for earth science application: a practical insight into production deployment M Maskey, R Ramachandran, I Gurung, B Freitag, JJ Miller, ... IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium …, 2019 | 12 | 2019 |
| Earth science deep learning: Applications and lessons learned M Maskey, R Ramachandran, JJ Miller, J Zhang, I Gurung IGARSS 2018-2018 IEEE International Geoscience and Remote Sensing Symposium …, 2018 | 12 | 2018 |
| Deep learning for phenomena-based classification of Earth science images M Maskey, R Ramachandran, J Miller Journal of Applied Remote Sensing 11 (4), 042608-042608, 2017 | 12 | 2017 |
| Advancing open science through innovative data system solutions: the joint ESA-NASA multi-mission algorithm and analysis platform (MAAP)'s data ecosystem K Bugbee, R Ramachandran, M Maskey, A Barciauskas, A Kaulfus, ... IGARSS 2020-2020 IEEE international geoscience and Remote sensing symposium …, 2020 | 9 | 2020 |
| Using deep learning for tropical cyclone intensity estimation J Miller, M Maskey, T Berendes AGU fall meeting abstracts 2017, IN11E-05, 2017 | 9 | 2017 |
| Simulation management systems developed by the Northern Gulf Coastal Hazards Collaboratory (NG-CHC): An overview of cyberinfrastructure to support the coastal modeling … RR Twilley, S Brandt, D Breaux, J Cartwright, J Chen, G Easson, ... Remote Sensing and Modeling: Advances in Coastal and Marine Resources, 365-394, 2014 | 9 | 2014 |