6 papers
Remote sensing data imputation using deep learning for multispectral imagery
Shuang Liu, Fiona Johnson, Rohitash Chandra
Remote sensing techniques have been increasingly utilised in aquatic applications in recent years. A common challenge in using optical satellite data is the presence of missing obs…
tBayes-MICE: A Bayesian Approach to Multiple Imputation for Time Series Data
Amuche Ibenegbu, Pierre Lafaye de Micheaux, Rohitash Chandra
Time-series analysis is often affected by missing data, a common problem across several fields, including healthcare and environmental monitoring. Multiple Imputation by Chained Eq…
Landcover classification and change detection using remote sensing and machine learning: a case study of Western Fiji
Yadvendra Gurjar, Ruoni Wan, Ehsan Farahbakhsh +1
As a developing country, Fiji is facing rapid urbanisation, which is visible in the massive development projects that include housing, roads, and civil works. In this study, we pre…
Convolutional neural networks for mineral prospecting through alteration mapping with remote sensing data
Ehsan Farahbakhsh, Dakshi Goel, Dhiraj Pimparkar +2
Traditional geological mapping, based on field observations and rock sample analysis, is inefficient for continuous spatial mapping of features like alteration zones. Deep learning…
Multi-Modal Deep Learning for Credit Rating Prediction Using Text and Numerical Data Streams
Mahsa Tavakoli, Rohitash Chandra, Fengrui Tian +1
Knowing which factors are significant in credit rating assignment leads to better decision-making. However, the focus of the literature thus far has been mostly on structured data,…
Recursive deep learning framework for forecasting the decadal world economic outlook
Tianyi Wang, Rodney Beard, John Hawkins +1
The gross domestic product (GDP) is the most widely used indicator in macroeconomics and the main tool for measuring a country's economic output. Due to the diversity and complexit…