Follow
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
902016
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
632017
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
492016
semBnet: a semantic Bayesian network for multivariate prediction of meteorological time series data
M Das, SK Ghosh
Pattern Recognition Letters 93, 192-201, 2017
452017
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
442017
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
422019
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
402014
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
362017
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
292017
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
262019
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
192016
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, 665-696, 2020
142020
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
142019
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
142015
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
132017
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
122020
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
122017
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
122014
Remote sensing scene classification under scarcity of labelled samples—A survey of the state-of-the-arts
S Dutta, M Das
Computers & Geosciences, 105295, 2023
112023
Enhanced Bayesian network models for spatial time series prediction
M Das, SK Ghosh
Springer International Publishing, 2020
112020
The system can't perform the operation now. Try again later.
Articles 1–20