24 citations · 27 across the 6 of their papers we have counts for
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cs.CV2019★ 24 cited
Conditional Generative Adversarial Networks for Data Augmentation and Adaptation in Remotely Sensed Imagery
Jonathan Howe, Kyle Pula, Aaron A. Reite
The difficulty in obtaining labeled data relevant to a given task is among the most common and well-known practical obstacles to applying deep learning techniques to new or even sl…
cs.CV2019★ 3 cited
Unsupervised Feature Learning in Remote Sensing
Aaron Reite, Scott Kangas, Zackery Steck +3
The need for labeled data is among the most common and well-known practical obstacles to deploying deep learning algorithms to solve real-world problems. The current generation of…