Monidipa Das
Orcid: 0000-0002-7615-4407Affiliations:
- Nanyang Technological University, Singapore
According to our database1,
Monidipa Das
authored at least 43 papers
between 2015 and 2024.
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Bibliography
2024
Multim. Tools Appl., February, 2024
IEEE Geosci. Remote. Sens. Lett., 2024
2023
GrapHiSM: a graph-based hierarchical semantics-driven model for aerial scene classification under scarcity of labelled samples.
Appl. Intell., November, 2023
An autonomous lightweight model for aerial scene classification under labeled sample scarcity.
Appl. Intell., October, 2023
SoURA: a user-reliability-aware social recommendation system based on graph neural network.
Neural Comput. Appl., September, 2023
Remote sensing scene classification under scarcity of labelled samples - A survey of the state-of-the-arts.
Comput. Geosci., February, 2023
Proceedings of the First Tiny Papers Track at ICLR 2023, 2023
2022
A Multilayered Adaptive Recurrent Incremental Network Model for Heterogeneity-Aware Prediction of Derived Remote Sensing Image Time Series.
IEEE Trans. Geosci. Remote. Sens., 2022
Statistical and Machine Learning Models for Remote Sensing Data Mining - Recent Advancements.
Remote. Sens., 2022
Neurocomputing, 2022
Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
2021
Reducing Parameter Value Uncertainty in Discrete Bayesian Network Learning: A Semantic Fuzzy Bayesian Approach.
IEEE Trans. Emerg. Top. Comput. Intell., 2021
Does Climate Variability Impact COVID-19 Outbreak? An Enhanced Semantics-Driven Theory-Guided Model.
SN Comput. Sci., 2021
Real-time prediction of spatial raster time series: a context-aware autonomous learning model.
J. Real Time Image Process., 2021
Analyzing impact of parental occupation on child's learning performance: a semantics-driven probabilistic approach.
Int. J. Data Sci. Anal., 2021
SELFIE: A Semantically-Enhanced Load Forecasting Approach with Indirect Estimate of Spatial Influences.
Proceedings of the IEEE Region 10 Conference, 2021
Analyzing Impact of Climate Variability on COVID-19 Outbreak: A Semantically-enhanced Theory-guided Data-driven Approach.
Proceedings of the CODS-COMAD 2021: 8th ACM IKDD CODS and 26th COMAD, 2021
2020
Enhanced Bayesian Network Models for Spatial Time Series Prediction - Recent Research Trend in Data-Driven Predictive Analytics
Studies in Computational Intelligence 858, Springer, ISBN: 978-3-030-27749-9, 2020
SARDINE: A Self-Adaptive Recurrent Deep Incremental Network Model for Spatio-Temporal Prediction of Remote Sensing Data.
ACM Trans. Spatial Algorithms Syst., 2020
Data-Driven Approaches for Spatio-Temporal Analysis: A Survey of the State-of-the-Arts.
J. Comput. Sci. Technol., 2020
A Self-Evolving Mutually-Operative Recurrent Network-based Model for Online Tool Condition Monitoring in Delay Scenario.
Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020
Online Prediction of Derived Remote Sensing Image Time Series: An Autonomous Machine Learning Approach.
Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 2020
A Skip-Connected Evolving Recurrent Neural Network for Data Stream Classification under Label Latency Scenario.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020
2019
FB-STEP: A fuzzy Bayesian network based data-driven framework for spatio-temporal prediction of climatological time series data.
Expert Syst. Appl., 2019
FERNN: A Fast and Evolving Recurrent Neural Network Model for Streaming Data Classification.
Proceedings of the International Joint Conference on Neural Networks, 2019
MUSE-RNN: A Multilayer Self-Evolving Recurrent Neural Network for Data Stream Classification.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019
Short-Term Load Forecasting: An Intelligent Approach Based on Recurrent Neural Network.
Proceedings of the Hybrid Intelligent Systems, 2019
Space-time Prediction of High Resolution Raster Data: An Approach based on Spatio-temporal Bayesian Network (STBN).
Proceedings of the ACM India Joint International Conference on Data Science and Management of Data, 2019
2018
Data-driven approaches for meteorological time series prediction: A comparative study of the state-of-the-art computational intelligence techniques.
Pattern Recognit. Lett., 2018
FORWARD: A Model for FOrecasting Reservoir WAteR Dynamics Using Spatial Bayesian Network (SpaBN) (Extended Abstract).
Proceedings of the 34th IEEE International Conference on Data Engineering, 2018
2017
FORWARD: A Model for FOrecasting Reservoir WAteR Dynamics Using Spatial Bayesian Network (SpaBN).
IEEE Trans. Knowl. Data Eng., 2017
A Deep-Learning-Based Forecasting Ensemble to Predict Missing Data for Remote Sensing Analysis.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017
Measuring Moran's I in a Cost-Efficient Manner to Describe a Land-Cover Change Pattern in Large-Scale Remote Sensing Imagery.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2017
semBnet: A semantic Bayesian network for multivariate prediction of meteorological time series data.
Pattern Recognit. Lett., 2017
Spatio-Temporal Prediction of Meteorological Time Series Data: An Approach Based on Spatial Bayesian Network (SpaBN).
Proceedings of the Pattern Recognition and Machine Intelligence, 2017
Spatio-temporal Prediction under Scarcity of Influencing Variables: A Hybrid Probabilistic Graph-based Approach.
Proceedings of the Ninth International Conference on Advances in Pattern Recognition, 2017
BESTED: An Exponentially Smoothed Spatial Bayesian Analysis Model for Spatio-temporal Prediction of Daily Precipitation.
Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2017
Spatio-temporal Autocorrelation Analysis for Regional Land-cover Change Detection from Remote Sensing Data.
Proceedings of the Fourth ACM IKDD Conferences on Data Sciences, 2017
2016
Deep-STEP: A Deep Learning Approach for Spatiotemporal Prediction of Remote Sensing Data.
IEEE Geosci. Remote. Sens. Lett., 2016
A cost-efficient approach for measuring Moran's index of spatial autocorrelation in geostationary satellite data.
Proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, 2016
Prediction of meteorological parameters: an a-posteriori probabilistic semantic kriging approach.
Proceedings of the 24th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2016, Burlingame, California, USA, October 31, 2016
Proceedings of the 3rd IKDD Conference on Data Science, 2016
2015
Detection of climate zones using multifractal detrended cross-correlation analysis: A spatio-temporal data mining approach.
Proceedings of the Eighth International Conference on Advances in Pattern Recognition, 2015