| Deep-STEP: A deep learning approach for spatiotemporal prediction of remote sensing data M Das, SK Ghosh IEEE Geoscience and Remote Sensing Letters 13 (12), 1984-1988, 2016 | 100 | 2016 |
| A deep-learning-based forecasting ensemble to predict missing data for remote sensing analysis M Das, SK Ghosh IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2017 | 71 | 2017 |
| A probabilistic nonlinear model for forecasting daily water level in reservoir M Das, SK Ghosh, VM Chowdary, A Saikrishnaveni, RK Sharma Water Resources Management 30, 3107-3122, 2016 | 56 | 2016 |
| semBnet: a semantic Bayesian network for multivariate prediction of meteorological time series data M Das, SK Ghosh Pattern Recognition Letters 93, 192-201, 2017 | 53 | 2017 |
| FB-STEP: a fuzzy Bayesian network based data-driven framework for spatio-temporal prediction of climatological time series data M Das, SK Ghosh Expert Systems with Applications 117, 211-227, 2019 | 47 | 2019 |
| Data-driven approaches for meteorological time series prediction: A comparative study of the state-of-the-art computational intelligence techniques M Das, SK Ghosh Pattern Recognit Letters, 1-10, 2017 | 47 | 2017 |
| A probabilistic approach for weather forecast using spatio-temporal inter-relationships among climate variables M Das, SK Ghosh 2014 9th International Conference on Industrial and Information Systems …, 2014 | 45 | 2014 |
| Measuring Moran's I in a cost-efficient manner to describe a land-cover change pattern in large-scale remote sensing imagery M Das, SK Ghosh IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2017 | 43 | 2017 |
| Muse-rnn: A multilayer self-evolving recurrent neural network for data stream classification M Das, M Pratama, S Savitri, J Zhang 2019 IEEE International Conference on Data Mining (ICDM), 110-119, 2019 | 30 | 2019 |
| FORWARD: a model for forecasting reservoir water dynamics using spatial Bayesian network (SpaBN) M Das, SK Ghosh, P Gupta, VM Chowdary, R Nagaraja, VK Dadhwal IEEE Transactions on Knowledge and Data Engineering 29 (4), 842-855, 2017 | 30 | 2017 |
| Data-driven approaches for spatio-temporal analysis: A survey of the state-of-the-arts M Das, SK Ghosh Journal of Computer Science and Technology 35 (3), 665-696, 2020 | 20 | 2020 |
| A cost-efficient approach for measuring Moran's index of spatial autocorrelation in geostationary satellite data M Das, SK Ghosh 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2016 | 19 | 2016 |
| Detection of climate zones using multifractal detrended cross-correlation analysis: A spatio-temporal data mining approach M Das, SK Ghosh 2015 Eighth International Conference on Advances in Pattern Recognition …, 2015 | 16 | 2015 |
| A skip-connected evolving recurrent neural network for data stream classification under label latency scenario M Das, M Pratama, J Zhang, YS Ong Proceedings of the AAAI Conference on artificial intelligence 34 (04), 3717-3724, 2020 | 15 | 2020 |
| Remote sensing scene classification under scarcity of labelled samples—A survey of the state-of-the-arts S Dutta, M Das Computers & Geosciences 171, 105295, 2023 | 14 | 2023 |
| FERNN: A fast and evolving recurrent neural network model for streaming data classification M Das, M Pratama, A Ashfahani, S Samanta 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 14 | 2019 |
| Spatio-temporal prediction of meteorological time series data: an approach based on spatial Bayesian network (SpaBN) M Das, SK Ghosh Pattern Recognition and Machine Intelligence: 7th International Conference …, 2017 | 13 | 2017 |
| Short-term prediction of land surface temperature using multifractal detrended fluctuation analysis M Das, SK Ghosh 2014 Annual IEEE India Conference (INDICON), 1-6, 2014 | 13 | 2014 |
| BESTED: An exponentially smoothed spatial Bayesian analysis model for spatio-temporal prediction of daily precipitation M Das, SK Ghosh Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances …, 2017 | 12 | 2017 |
| Enhanced Bayesian network models for spatial time series prediction M Das, SK Ghosh Springer International Publishing, 2020 | 11 | 2020 |
