72 citations · 156 across the 11 of their papers we have counts for
11 papers
GenCo: An Auxiliary Generator from Contrastive Learning for Enhanced Few-Shot Learning in Remote Sensing
Jing Wu, Naira Hovakimyan, Jennifer Hobbs
Classifying and segmenting patterns from a limited number of examples is a significant challenge in remote sensing and earth observation due to the difficulty in acquiring accurate…
Hallucination Improves the Performance of Unsupervised Visual Representation Learning
Jing Wu, Jennifer Hobbs, Naira Hovakimyan
Contrastive learning models based on Siamese structure have demonstrated remarkable performance in self-supervised learning. Such a success of contrastive learning relies on two co…
Extended Agriculture-Vision: An Extension of a Large Aerial Image Dataset for Agricultural Pattern Analysis
Jing Wu, David Pichler, Daniel Marley +3
A key challenge for much of the machine learning work on remote sensing and earth observation data is the difficulty in acquiring large amounts of accurately labeled data. This is…
Superpixels and Graph Convolutional Neural Networks for Efficient Detection of Nutrient Deficiency Stress from Aerial Imagery
Saba Dadsetan, David Pichler, David Wilson +2
Advances in remote sensing technology have led to the capture of massive amounts of data. Increased image resolution, more frequent revisit times, and additional spectral channels…
Residue Density Segmentation for Monitoring and Optimizing Tillage Practices
Jennifer Hobbs, Ivan Dozier, Naira Hovakimyan
"No-till" and cover cropping are often identified as the leading simple, best management practices for carbon sequestration in agriculture. However, the root of the problem is more…
Detection and Prediction of Nutrient Deficiency Stress using Longitudinal Aerial Imagery
Saba Dadsetan, Gisele Rose, Naira Hovakimyan +1
Early, precise detection of nutrient deficiency stress (NDS) has key economic as well as environmental impact; precision application of chemicals in place of blanket application re…
The 1st Agriculture-Vision Challenge: Methods and Results
Mang Tik Chiu, Xingqian Xu, Kai Wang +39
The first Agriculture-Vision Challenge aims to encourage research in developing novel and effective algorithms for agricultural pattern recognition from aerial images, especially f…
Improved Structural Discovery and Representation Learning of Multi-Agent Data
Jennifer Hobbs, Matthew Holbrook, Nathan Frank +2
Central to all machine learning algorithms is data representation. For multi-agent systems, selecting a representation which adequately captures the interactions among agents is ch…
Rugby-Bot: Utilizing Multi-Task Learning & Fine-Grained Features for Rugby League Analysis
Matthew Holbrook, Jennifer Hobbs, Patrick Lucey
Sporting events are extremely complex and require a multitude of metrics to accurate describe the event. When making multiple predictions, one should make them from a single source…
Generating Long-term Trajectories Using Deep Hierarchical Networks
Stephan Zheng, Yisong Yue, Patrick Lucey
We study the problem of modeling spatiotemporal trajectories over long time horizons using expert demonstrations. For instance, in sports, agents often choose action sequences with…
Demonstration of Communication using Neutrinos
D. D. Stancil, P. Adamson, M. Alania +109
Beams of neutrinos have been proposed as a vehicle for communications under unusual circumstances, such as direct point-to-point global communication, communication with submarines…