6 citations · 21 across the 7 of their papers we have counts for
11 papers
GeoAI at ACM SIGSPATIAL: The New Frontier of Geospatial Artificial Intelligence Research
Dalton Lunga, Yingjie Hu, Shawn Newsam +4
Geospatial Artificial Intelligence (GeoAI) is an interdisciplinary field enjoying tremendous adoption. However, the efficient design and implementation of GeoAI systems face many o…
DistPro: Searching A Fast Knowledge Distillation Process via Meta Optimization
Xueqing Deng, Dawei Sun, Shawn Newsam +1
Recent Knowledge distillation (KD) studies show that different manually designed schemes impact the learned results significantly. Yet, in KD, automatically searching an optimal di…
NightLab: A Dual-level Architecture with Hardness Detection for Segmentation at Night
Xueqing Deng, Peng Wang, Xiaochen Lian +1
The semantic segmentation of nighttime scenes is a challenging problem that is key to impactful applications like self-driving cars. Yet, it has received little attention compared…
AutoAdapt: Automated Segmentation Network Search for Unsupervised Domain Adaptation
Xueqing Deng, Yi Zhu, Yuxin Tian +1
Neural network-based semantic segmentation has achieved remarkable results when large amounts of annotated data are available, that is, in the supervised case. However, such data i…
Scale Aware Adaptation for Land-Cover Classification in Remote Sensing Imagery
Xueqing Deng, Yi Zhu, Yuxin Tian +1
Land-cover classification using remote sensing imagery is an important Earth observation task. Recently, land cover classification has benefited from the development of fully conne…
Using Conditional Generative Adversarial Networks to Generate Ground-Level Views From Overhead Imagery
Xueqing Deng, Yi Zhu, Shawn Newsam
This paper develops a deep-learning framework to synthesize a ground-level view of a location given an overhead image. We propose a novel conditional generative adversarial network…