Monidipa Das
Monidipa Das
Postdoctoral Research Fellow, School of CSE, NTU Singapore
Verified email at ntu.edu.sg - Homepage
Title
Cited by
Cited by
Year
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
402016
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 (9), 3107-3122, 2016
262016
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
242014
semBnet: a semantic Bayesian network for multivariate prediction of meteorological time series data
M Das, SK Ghosh
Pattern Recognition Letters 93, 192-201, 2017
222017
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
222017
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
212017
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
192019
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
152017
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
102016
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
102015
Prediction of meteorological parameters: an a-posteriori probabilistic semantic kriging approach
S Bhattacharjee, M Das, SK Ghosh, S Shekhar
Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances …, 2016
92016
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
92014
Spatio-temporal prediction under scarcity of influencing variables: a hybrid probabilistic graph-based approach
M Das, SK Ghosh
2017 Ninth International Conference on Advances in Pattern Recognition …, 2017
82017
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
82017
Spatio-temporal prediction of meteorological time series data: an approach based on spatial Bayesian network (SpaBN)
M Das, SK Ghosh
International Conference on Pattern Recognition and Machine Intelligence …, 2017
72017
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
72017
Space-time prediction of high resolution raster data: An approach based on spatio-temporal Bayesian network (STBN)
M Das, SK Ghosh
Proceedings of the ACM India Joint International Conference on Data Science …, 2019
42019
Performance analysis for nfbn—a new fuzzy Bayesian network learning approach
M Das, SK Ghosh
Recent Findings in Intelligent Computing Techniques, 363-376, 2018
42018
Spatio-temporal autocorrelation analysis for regional land-cover change detection from remote sensing data
M Das, SK Ghosh
Proceedings of the Fourth ACM IKDD Conferences on Data Sciences, 1-10, 2017
42017
Modeling spatio-temporal change pattern using mathematical morphology
M Das, SK Ghosh
Proceedings of the 3rd IKDD Conference on Data Science, 2016, 1-10, 2016
42016
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Articles 1–20