56 citations · 149 across the 7 of their papers we have counts for
12 papers
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…
Measurement of and with a semileptonic tagging method
The Belle Collaboration, G. Caria, P. Urquijo +188
The experimental results on the ratios of branching fractions and $\mathcal{R}(D^…
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…
Measurement of the CKM Matrix Element from at Belle
E. Waheed, P. Urquijo, I. Adachi +184
We present a new measurement of the CKM matrix element from decays, reconstructed with the full Belle data set of i…
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 (…
DeepSD: Generating High Resolution Climate Change Projections through Single Image Super-Resolution
Thomas Vandal, Evan Kodra, Sangram Ganguly +3
The impacts of climate change are felt by most critical systems, such as infrastructure, ecological systems, and power-plants. However, contemporary Earth System Models (ESM) are r…