56 citations · 112 across the 5 of their papers we have counts for
8 papers
Spectral Synthesis for Satellite-to-Satellite Translation
Thomas Vandal, Daniel McDuff, Weile Wang +2
Earth observing satellites carrying multi-spectral sensors are widely used to monitor the physical and biological states of the atmosphere, land, and oceans. These satellites have…
High-Dimensional Similarity Search with Quantum-Assisted Variational Autoencoder
Nicholas Gao, Max Wilson, Thomas Vandal +3
Recent progress in quantum algorithms and hardware indicates the potential importance of quantum computing in the near future. However, finding suitable application areas remains a…
DeepSat V2: Feature Augmented Convolutional Neural Nets for Satellite Image Classification
Qun Liu, Saikat Basu, Sangram Ganguly +4
Satellite image classification is a challenging problem that lies at the crossroads of remote sensing, computer vision, and machine learning. Due to the high variability inherent i…
Temporal Interpolation of Geostationary Satellite Imagery with Task Specific Optical Flow
Thomas Vandal, Ramakrishna Nemani
Applications of satellite data in areas such as weather tracking and modeling, ecosystem monitoring, wildfire detection, and land-cover change are heavily dependent on the trade-of…
Progressively Growing Generative Adversarial Networks for High Resolution Semantic Segmentation of Satellite Images
Edward Collier, Kate Duffy, Sangram Ganguly +8
Machine learning has proven to be useful in classification and segmentation of images. In this paper, we evaluate a training methodology for pixel-wise segmentation on high resolut…
Quantifying Uncertainty in Discrete-Continuous and Skewed Data with Bayesian Deep Learning
Thomas Vandal, Evan Kodra, Jennifer Dy +3
Deep Learning (DL) methods have been transforming computer vision with innovative adaptations to other domains including climate change. For DL to pervade Science and Engineering (…