56 citations · 163 across the 10 of their papers we have counts for
4 papers · 1 filter
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…
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…
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…
A Theoretical Analysis of Deep Neural Networks for Texture Classification
Saikat Basu, Manohar Karki, Robert DiBiano +4
We investigate the use of Deep Neural Networks for the classification of image datasets where texture features are important for generating class-conditional discriminative represe…